------------------------------------------------------------------------------------------------------------------------------------------------
      name:  <unnamed>
       log:  C:\Users\locasa\Dropbox\Patriotism\writeup\submission\QJE\replication\log/results-main.log
  log type:  text
 opened on:  15 Jun 2022, 15:22:58

. 
. mkdir tmp/

. 
. *       Patriotism!
. 
. *       FIRST VERSION  June            2, 2022
. *       THIS VERSION   June        2, 2022
. *       LAST RUN       January     2, 2022
. 
. *       AUTHOR              AT
. *       LAST REVISOR            
. 
. *       Log of revisions:
. 
. *       This produces tables and figures in the main text
. 
. ***************************************************************************************************
. ****                              PLAN OF THE PROCEDURE                                        ****
. ****___________________________________________________________________________________________****
. ****                                                                                           ****
. ****     I. Tables                                                                             ****
. ****         Tab 1. Summary statistics                                                         ****
. ****         Tab 2. New Deal and Patriotism: Basic Patterns                                    ****
. ****                    a. Panel A                                                                                     ****
. ****                    b. Panel B                                                                                     ****
. ****         Tab 3. New Deal Support and Patriotism: Individual-Level Results                  ****
. ****              a. Panel D                                                                                       ****
. ****         Tab 4. Identification                                                                                 ****
. ****         Tab 5. Identification: Individual level                                                   ****
. ****     II. Figures                                                                           ****
. ****         Fig 1. New Deal Spending and WW II Patriotis                                                  ****
. ****         Fig 2. Geographic Distribution of Main Variables                                          ****
. ****                    a. War bonds                                                                               ****
. ****                    b. Volunteers                                                              ****
. ****                    c. Medals                                                                                  ****
. ****                    d. New Deal grants                                                                     ****
. ****                    e. Agricultural support                                                                    ****
. ****                    f. Droughts                                                                                ****
. ****         Fig 3. Identification                                                                                                     ****
. ****                    a. Droughts                                                                            ****
. ****                    b. Committees                                                                      ****
. ****         Fig 4. Pre-New Deal Droughts                                                                                              ****
. ****                a. Droughts and AAA spending overtime                                                      ****
. ****                b. Patriotism and pre-New Deal droughts                                                ****
. ****     III. Erase junk                                                                       ****
. ****___________________________________________________________________________________________****
. ***************************************************************************************************
. 
. macro def control                        "ww1_vol_sh ww1_awards_pop10_is lpop30 c30unemp c30urban1 c30farm iYf_T29 MEAN9628 c30men c30black c3
> 0jap c30deu c30ita c30vet lc40wage iwarconpro_PC i.stateicpsr"

. macro def controls_asn       "h w bmi C40NONWHITE C40MARRIED noncitizen C40SCHOOL_E  C40SCHOOL_H C40SCHOOL_C i.C40AGE"

. macro def controls_asn_noage "h w bmi C40NONWHITE C40MARRIED noncitizen C40SCHOOL_E  C40SCHOOL_H C40SCHOOL_C"

. 
. ********************************************************************************
. ****           0. Prepare datasets                                          ****
. ****                    i. ASN                                                      ****
. ******************************************************************************** 
. 
. use "data/patriotism-ASN", clear

. 
. lab var iAAA_PF_farmer                                   "AAA grants $\times$ farmer"

. lab var iAAA_PF_farmhand                                 "AAA grants $\times$ farm-hand"

. lab var iSUM3MO_DROUGHT3340_farmer       "Summer droughts: 1933-40 $\times$ farmer"

. lab var iAGRI_T73_farmer                                 "Tenure in Agri committee: 1933-35 $\times$ farmer"

. lab var iSUM3MO_DROUGHT3340_farmhand     "Summer droughts: 1933-40 $\times$ farm-hand"

. lab var iAGRI_T73_farmhand                       "Tenure in Agri committee: 1933-35 $\times$ farm-hand"

. lab var farmer                                                   "Farmer"

. lab var farmhand                                                 "Farm-hand"

. 
. save "tmp/asn", replace
(note: file tmp/asn.dta not found)
file tmp/asn.dta saved

. 
. ********************************************************************************
. ****                    ii. Main                                                    ****
. ********************************************************************************   
. use "data\patriotism", clear

. 
. lab var lpop30                  "log 1930 population"

. lab var c30unemp            "1930 unemployment rate"

. lab var c40unemp            "1940 unemployment rate"

. lab var lc40wage                "log 1939 average wage"

. lab var c30urban1           "Urban status: 1930"

. lab var MEAN9628                "Mean Democratic vote share: 1898-1928"

. lab var c30men                  "1930 share of men"

. lab var c30black                "1930 share of blacks"

. lab var c30jap                  "1930 share of Japaneses"

. lab var c30deu                  "1930 share of Germans"

. lab var c30ita                  "1930 share of Italians"

. lab var c30vet                  "1930 share of veterans"

. lab var invpop_w99              "Inverse of 1930 population"

. lab var c30farm                 "1930 farm share"

. lab var iwarbond_1944_PC    "1944 war bond purchases p.c." 

. lab var ww2_vol_pop40       "WWII volunteers per 1940 population"

. lab var iwarconpro_PC       "WII war contract per capita"

. lab var ww1_vol_sh          "WWI volunteering rate"

. lab var ww1_vol_pop10       "WWI volunteers per capita"

. lab var ww1_awards_pop10_is "WWI awards per capita"

. lab var iYf_T29             "1929 farm income"

. lab var shown_1930          "1930 share of farm-owners"

. lab var iSUM3MO_DROUGHT3340 "Months of drought: 1933-40"

. lab var iAGRI_T62           "Tenure agri committee: 1911-13"

. lab var iAGRI_T73           "Tenure agri committee: 1933-35"

. lab var iHOLC_PH            "HOLC loans"

. lab var iinfra_AL           "Public works grants"

. lab var iRFC_PC             "RFC loans"

. lab var iNDEXP_PC               "New Deal grants"

. lab var iSSA_PB                 "Public Assistance"

. lab var iAGRI_PF                "Agricultural support"

. lab var EW_AL                   "Emergency workers"

. lab var tye_tfe890_500k_100_l6 "Frontier experience"

. lab var ww2_awards_pop40_is "WWII medals per 1940 population"

. 
. save "tmp/patriot", replace
(note: file tmp/patriot.dta not found)
file tmp/patriot.dta saved

. 
. do "code-build/01_Shopping_List.do"

. *       Patriotism!
. 
. *       FIRST VERSION  June       13, 2022
. *       THIS VERSION   June       13, 2022
. *       LAST RUN       June       13, 2022
. 
. *       LAST REVISOR            LMC
. 
. *       Log of revisions:
. 
. *       This prepares all the Packages for you to run smoothly the replicator
. *       
. *               WARNING: THIS IS NOT A STANDALONE FILE, IT WILL BE RUN IN EACH FILE!
. 
. ********************************************************************************
. ****                      PLAN OF THE PROCEDURE                             ****
. ****                                                                        ****
. ****    1. Creating the Shopping List                                           ****
. ********************************************************************************
. local dir : pwd

. 
. sysdir set PLUS "`dir'\ado"

. 
end of do-file

. 
. ***************************************************************************************************
. ****     I. Tables                                                                             ****
. ****         Tab 1. Summary statistics                                                         ****
. ***************************************************************************************************
. use "tmp/patriot", replace

. 
. preserve

.         replace ww2_vol_pop40       = . if servicecommand == 7
(707 real changes made, 707 to missing)

.         replace ww2_volw_pop40      = . if servicecommand == 7
(686 real changes made, 686 to missing)

.         replace ww2_awards_pop40_is = . if servicecommand == 7
(707 real changes made, 707 to missing)

.         
.         lab var iwarbond_1944_PC    "1944 war bond purchases p.c. (i.h.s.)"

.         lab var ww2_vol_pop40       "WWII volunteers per 1940 population ($\times$100)"

.         lab var ww2_awards_pop40_is "WWII medals per 1940 population ($\times$1000, i.h.s.)"

.         
.         lab var iNDEXP_PC           "New Deal grants per 1930 population (i.h.s.)"

.         lab var iAGRI_PF            "AAA grants and FCA loans per 1930 farmers (i.h.s.)"

.         lab var iSSA_PB             "Public assistance grants per beneficiary (i.h.s.)"

.         lab var EW_AL               "Emergency workers per worker (1938)"

.         lab var iinfra_AL           "Public works grants per worker (i.h.s.)"

.         lab var iHOLC_PH            "HOLC loans per 1930 home owners (i.h.s.)"

.         lab var iRFC_PC             "RFC loans per 1930 population (i.h.s.)"

.         
.         lab var iSUM3MO_DROUGHT3340 "Number of drought months: 1933-40 (i.h.s.)"

.         lab var iAGRI_T73           "Tenure in agricultural committee: 1933-35 (i.h.s.)"

.         
.         lab var ww1_vol_pop10       "WWI volunteers per 1910 population ($\times$ 100)"

.         lab var ww1_vol_sh          "WWI volunteer share"

.         lab var ww1_awards_pop10_is "WWI medals per 1910 population ($\times$1000, i.h.s.)"

.         
.         lab var MEAN9628            "Average vote share for the Democrats: 1898-1928"

.         lab var lpop30              "log 1930 population"

.         lab var c30urban1           "Urban status: 1930"

.         lab var iYf_T29             "1929 farm income"

.         lab var c30farm             "1930 farm share"

.         lab var shown_1930                      "1930 share of farm-owners"

.         lab var c30men              "1930 share of men"

.         lab var c30black            "1930 share of blacks"

.         lab var c30jap              "1930 share of Japaneses"

.         lab var c30deu              "1930 share of Germans"

.         lab var c30ita              "1930 share of Italians"

.         lab var c30vet              "1930 share of veterans"

.         
.         lab var c30unemp            "1930 unemployment rate"

.         lab var c40unemp            "1940 unemployment rate"

.         lab var lc40wage            "log 1939 average wage"

.         lab var iwarconpro_PC       "WWII war contract per capita (i.h.s.)"

.                         
.         estpost summarize iwarbond_1944_PC ww2_vol_pop40 ww2_awards_pop40_is ///
>         iNDEXP_PC iAGRI_PF iSSA_PB EW_AL iinfra_AL iHOLC_PH iRFC_PC ///
>         iSUM3MO_DROUGHT3340 iAGRI_T73 ///
>         ww1_vol_pop10 ww1_vol_sh ww1_awards_pop10_is ///
>         MEAN9628 lpop30 c30urban1 iYf_T29 c30farm shown_1930 c30men c30black c30jap c30deu c30ita c30vet ///
>         c30unemp c40unemp lc40wage iwarconpro_PC  if sample_ols == 1

             |  e(count)   e(sum_w)    e(mean)     e(Var)      e(sd)     e(min)     e(max)     e(sum) 
-------------+----------------------------------------------------------------------------------------
iwarbond_1~C |      3022       3022   4.657672   .4572168   .6761781          0   7.733282   14075.49 
ww2_vol_p~40 |      2329       2329   .6338998   .1168116   .3417772   7.22e-11   2.810051   1476.353 
ww2_awards~s |      2329       2329     .14027   .0162916   .1276384          0   2.522855   326.6889 
   iNDEXP_PC |      3022       3022   5.506974     .33453   .5783857   3.719078   8.962657   16642.08 
    iAGRI_PF |      3022       3022   6.634541   1.119513    1.05807          0   9.839973   20049.58 
     iSSA_PB |      3022       3022   5.884899   1.080167   1.039311          0   10.03439   17784.16 
       EW_AL |      3022       3022   .1966453    .008409   .0917007          0   .7358916   594.2621 
   iinfra_AL |      3022       3022   6.220155   1.426137    1.19421          0   11.94709   18797.31 
    iHOLC_PH |      3022       3022   3.089123   1.450234   1.204257          0   6.030134   9335.329 
     iRFC_PC |      3022       3022   2.639354   1.931864   1.389915          0   7.483077   7976.127 
iSUM3MO~3340 |      3022       3022   1.683102   1.434143   1.197557          0   3.784705   5086.333 
   iAGRI_T73 |      3022       3022   .1298102   .2116301   .4600327          0   2.644121   392.2865 
ww1_vol_p~10 |      3022       3022   .4317656   .2056035   .4534352          0   8.506153   1304.796 
  ww1_vol_sh |      3022       3022   .3535356   .0638807   .2527464          0          1   1068.385 
ww1_awards~s |      3022       3022   .0568125   .0084333   .0918328          0   1.634361   171.6875 
    MEAN9628 |      3022       3022   49.44964   343.6289   18.53723   7.466274   99.04321   149436.8 
      lpop30 |      3022       3022   9.827638    1.05865   1.028907   4.382027   15.74942   29699.12 
   c30urban1 |      3022       3022   .5469887   .2478741   .4978695          0          1       1653 
     iYf_T29 |      3022       3022   3.096202   .5180781   .7197764   .2753071   8.294127   9356.721 
     c30farm |      3022       3022   .4925268   .0510673   .2259808          0       .975   1488.416 
  shown_1930 |      3022       3022   .6126242   .0416807   .2041585   .0277236          1    1851.35 
      c30men |      3022       3022   .5167537   .0004799   .0219059     .46582   .7266697    1561.63 
    c30black |      3022       3022   .1116402   .0338915   .1840966          0   .8590472   337.3766 
      c30jap |      3022       3022   .0006826   .0000155   .0039357          0   .0768382   2.062761 
      c30deu |      3022       3022   .0443227   .0033647   .0580056          0   .3787545   133.9432 
      c30ita |      3022       3022   .0086249   .0005443     .02333          0   .2181965   26.06454 
      c30vet |      3022       3022   .1147634   .0013072   .0361555          0   .5829356   346.8149 
    c30unemp |      3022       3022    .059125   .0016262   .0403262          0   .5007864   178.6759 
    c40unemp |      3022       3022   .0687975   .0013325   .0365038          0   .3020996    207.906 
    lc40wage |      3022       3022   6.414985   .1109062   .3330259   5.294861   7.408122   19386.09 
iwarconpro~C |      3022       3022   .3179609    .364691   .6038965          0    4.80087   960.8777 

.         
.         esttab . using "results/tables/Tab1_summary.tex",                                                          ///
>                         cells("mean(fmt(%9.3f) label(Mean)) sd(fmt(%9.3f) label(St. dev.)) count(fmt(%9.0f) label(Obs.))") ///
>                         nonumber noobs replace label                                                                       ///
>                         b(%9.3f) se(%9.3f)                                                                                 ///
>                         title("Summary statistics.")
(output written to results/tables/Tab1_summary.tex)

. restore

. 
. ***************************************************************************************************
. ****     I. Tables                                                                             ****
. ****         Tab 2. New Deal and Patriotism: Basic Patterns                                    ****
. ****              a. Panel A                                                                                       ****
. ***************************************************************************************************
. estimates clear

. eststo: xi:  reg iwarbond_1944_PC   iNDEXP_PC $control if sample_ols == 1                      , r beta
i.stateicpsr      _Istateicps_1-98    (naturally coded; _Istateicps_1 omitted)
note: _Istateicps_98 omitted because of collinearity

Linear regression                               Number of obs     =      3,022
                                                F(64, 2957)       =      95.84
                                                Prob > F          =     0.0000
                                                R-squared         =     0.6500
                                                Root MSE          =     .40435

-------------------------------------------------------------------------------------
                    |               Robust
   iwarbond_1944_PC |      Coef.   Std. Err.      t    P>|t|                     Beta
--------------------+----------------------------------------------------------------
          iNDEXP_PC |   .1913998   .0240857     7.95   0.000                 .1637186
         ww1_vol_sh |  -.0037429   .0360486    -0.10   0.917                 -.001399
ww1_awards_pop10_is |   .2400123   .0841721     2.85   0.004                 .0325964
             lpop30 |  -.0296454   .0256091    -1.16   0.247                -.0451099
           c30unemp |  -.7161748   .2732509    -2.62   0.009                -.0427115
          c30urban1 |   .0752111   .0247794     3.04   0.002                 .0553779
            c30farm |  -.4194219    .125145    -3.35   0.001                -.1401721
            iYf_T29 |   .0884241   .0194234     4.55   0.000                 .0941255
           MEAN9628 |   .0034886   .0009676     3.61   0.000                 .0956385
             c30men |  -1.707234   .7532938    -2.27   0.024                -.0553088
           c30black |  -.2844474   .0859688    -3.31   0.001                -.0774438
             c30jap |   6.097407   2.218797     2.75   0.006                 .0354902
             c30deu |   .9365989   .1897416     4.94   0.000                 .0803457
             c30ita |  -.3709609   .5636864    -0.66   0.511                -.0127991
             c30vet |  -.0730453   1.021874    -0.07   0.943                -.0039058
           lc40wage |   .5192187   .0575798     9.02   0.000                 .2557215
      iwarconpro_PC |   .2594412   .0220916    11.74   0.000                 .2317076
      _Istateicps_2 |  -.1975357   .1281159    -1.54   0.123                -.0212039
      _Istateicps_3 |  -.2401156   .1259525    -1.91   0.057                -.0223363
      _Istateicps_4 |  -.1076083    .172976    -0.62   0.534                -.0091409
      _Istateicps_5 |  -.3589533   .3447272    -1.04   0.298                -.0215788
      _Istateicps_6 |  -.0434672   .1234164    -0.35   0.725                 -.004366
     _Istateicps_11 |   .1908367   .1453972     1.31   0.189                 .0088894
     _Istateicps_12 |  -.1411405   .1121733    -1.26   0.208                -.0173425
     _Istateicps_13 |  -.0702594   .0959957    -0.73   0.464                -.0142585
     _Istateicps_14 |  -.1039543    .100406    -1.04   0.301                -.0224741
     _Istateicps_21 |   .1002843   .1038924     0.97   0.334                  .026788
     _Istateicps_22 |   .0264737   .1034735     0.26   0.798                 .0067276
     _Istateicps_23 |  -.0683264   .1054779    -0.65   0.517                -.0165175
     _Istateicps_24 |  -.0883392    .102684    -0.86   0.390                -.0216039
     _Istateicps_25 |   .0197177     .11181     0.18   0.860                 .0043871
     _Istateicps_31 |   .6088195   .1088795     5.59   0.000                 .1595169
     _Istateicps_32 |   .4766987   .1132473     4.21   0.000                 .1261248
     _Istateicps_33 |   .3570563   .1147385     3.11   0.002                 .0878173
     _Istateicps_34 |  -.0190878   .1051365    -0.18   0.856                -.0053792
     _Istateicps_35 |   .5857538   .1136278     5.16   0.000                 .1480676
     _Istateicps_36 |   .6987652   .1322788     5.28   0.000                 .1356721
     _Istateicps_37 |    .389369   .1179493     3.30   0.001                 .0841786
     _Istateicps_40 |   .0178281    .117396     0.15   0.879                  .004717
     _Istateicps_41 |  -.0345923   .1128017    -0.31   0.759                -.0074786
     _Istateicps_42 |  -.4192116   .1196381    -3.50   0.000                -.0964651
     _Istateicps_43 |  -.1057771    .130009    -0.81   0.416                -.0226981
     _Istateicps_44 |  -.1549352   .1167353    -1.33   0.185                -.0508603
     _Istateicps_45 |  -.2966653   .1194827    -2.48   0.013                -.0631789
     _Istateicps_46 |  -.1482086   .1213463    -1.22   0.222                -.0356181
     _Istateicps_47 |  -.1095101   .1120281    -0.98   0.328                -.0288338
     _Istateicps_48 |   -.437282   .1303906    -3.35   0.001                -.0791905
     _Istateicps_49 |   .1502483   .1131627     1.33   0.184                 .0609965
     _Istateicps_51 |   -.345749   .1094068    -3.16   0.002                -.0998658
     _Istateicps_52 |  -.0976841   .1351856    -0.72   0.470                -.0122832
     _Istateicps_53 |   .0693364   .1162262     0.60   0.551                 .0161609
     _Istateicps_54 |  -.1821322   .1090789    -1.67   0.095                -.0470085
     _Istateicps_56 |  -.3038139   .1072261    -2.83   0.005                -.0600709
     _Istateicps_61 |  -.1599922   .1506209    -1.06   0.288                -.0148829
     _Istateicps_62 |   .0183581   .1223038     0.15   0.881                 .0038493
     _Istateicps_63 |   .1454593   .1371795     1.06   0.289                 .0254816
     _Istateicps_64 |    .581984   .1317018     4.42   0.000                 .1119457
     _Istateicps_65 |  -.0463904   .1762576    -0.26   0.792                -.0051321
     _Istateicps_66 |  -.2784062   .1488858    -1.87   0.062                -.0394548
     _Istateicps_67 |  -.1397665   .1296454    -1.08   0.281                -.0201545
     _Istateicps_68 |   .4239373   .1449069     2.93   0.003                 .0544967
     _Istateicps_71 |   .1904838   .1211077     1.57   0.116                 .0386569
     _Istateicps_72 |   .5718963   .1252598     4.57   0.000                 .0917761
     _Istateicps_73 |   .3760192   .1560744     2.41   0.016                 .0619751
     _Istateicps_98 |          0  (omitted)                                         .
              _cons |   1.061665   .5962388     1.78   0.075                        .
-------------------------------------------------------------------------------------
(est1 stored)

. estadd local betacoef   = string(r(PT)[1,6], "%9.3f")

added macro:
           e(betacoef) : "0.164"

. 
.             qui: sum iwarbond_1944_PC   if e(sample) == 1, d

. estadd local y_mean_round = string(r(mean), "%9.3f")

added macro:
       e(y_mean_round) : "4.658"

.        local iqr_y       = (r(p75) - r(p25))

. estadd local IQR_Y = string(`iqr_y', "%9.3f")

added macro:
              e(IQR_Y) : "0.921"

.             qui: sum iNDEXP_PC          if e(sample) == 1, d

.        local iqr_x       = (r(p75) - r(p25))

. estadd local IQR_X = string(`iqr_x', "%9.3f")

added macro:
              e(IQR_X) : "0.713"

. 
.            local IQR_Xbeta    = `iqr_x'*_b[iNDEXP_PC]

. estadd local sIQR_Xbeta   = string(`IQR_Xbeta', "%9.3f")

added macro:
         e(sIQR_Xbeta) : "0.136"

. 
.            local IQR_XbetadY  = (`IQR_Xbeta'/`iqr_y')*100

. estadd local sIQR_XbetadY = string(`IQR_XbetadY', "%9.1f") + "\%"

added macro:
       e(sIQR_XbetadY) : "14.8\%"

. 
. eststo: xi:  reg ww2_vol_pop40      iNDEXP_PC $control if sample_ols == 1 & servicecommand != 7, r beta
i.stateicpsr      _Istateicps_1-98    (naturally coded; _Istateicps_1 omitted)
note: _Istateicps_31 omitted because of collinearity
note: _Istateicps_32 omitted because of collinearity
note: _Istateicps_33 omitted because of collinearity
note: _Istateicps_34 omitted because of collinearity
note: _Istateicps_35 omitted because of collinearity
note: _Istateicps_36 omitted because of collinearity
note: _Istateicps_37 omitted because of collinearity
note: _Istateicps_62 omitted because of collinearity
note: _Istateicps_68 omitted because of collinearity
note: _Istateicps_98 omitted because of collinearity

Linear regression                               Number of obs     =      2,329
                                                F(55, 2273)       =      70.72
                                                Prob > F          =     0.0000
                                                R-squared         =     0.6198
                                                Root MSE          =     .21328

-------------------------------------------------------------------------------------
                    |               Robust
      ww2_vol_pop40 |      Coef.   Std. Err.      t    P>|t|                     Beta
--------------------+----------------------------------------------------------------
          iNDEXP_PC |   .0471713   .0156551     3.01   0.003                 .0759638
         ww1_vol_sh |    .110829   .0259825     4.27   0.000                 .0788984
ww1_awards_pop10_is |   .1295866    .099245     1.31   0.192                 .0351886
             lpop30 |  -.0150495   .0103258    -1.46   0.145                -.0460348
           c30unemp |   .5311241   .1977125     2.69   0.007                 .0643222
          c30urban1 |   .0166562    .012915     1.29   0.197                 .0240678
            c30farm |  -.0670716   .0536509    -1.25   0.211                -.0465073
            iYf_T29 |  -.0200108   .0111169    -1.80   0.072                -.0426069
           MEAN9628 |   .0000689    .000535     0.13   0.898                 .0038779
             c30men |  -1.373568   .5151439    -2.67   0.008                -.0906114
           c30black |  -.4372501   .0382799   -11.42   0.000                -.2550194
             c30jap |   .8435633   1.227346     0.69   0.492                 .0106152
             c30deu |  -.6184738    .159494    -3.88   0.000                -.0850189
             c30ita |  -.2575304   .2393845    -1.08   0.282                -.0191439
             c30vet |   1.064258   .3284924     3.24   0.001                 .1103828
           lc40wage |   .2232951   .0331382     6.74   0.000                 .2307347
      iwarconpro_PC |  -.0386987   .0079706    -4.86   0.000                 -.071751
      _Istateicps_2 |  -.0346837   .0607441    -0.57   0.568                 -.008384
      _Istateicps_3 |   .0179922   .0595143     0.30   0.762                 .0037698
      _Istateicps_4 |   .2100558   .0793067     2.65   0.008                 .0401944
      _Istateicps_5 |   -.020517   .0692617    -0.30   0.767                -.0027791
      _Istateicps_6 |   .2849785   .0778868     3.66   0.000                 .0644662
     _Istateicps_11 |  -.1905889    .063374    -3.01   0.003                -.0200052
     _Istateicps_12 |  -.1088452   .0537399    -2.03   0.043                -.0301105
     _Istateicps_13 |   .0184302   .0534532     0.34   0.730                 .0084049
     _Istateicps_14 |  -.2415148   .0518837    -4.65   0.000                 -.117284
     _Istateicps_21 |   .0194748   .0574804     0.34   0.735                 .0116631
     _Istateicps_22 |  -.0834092   .0557229    -1.50   0.135                -.0475468
     _Istateicps_23 |  -.0520224     .06226    -0.84   0.403                -.0282238
     _Istateicps_24 |  -.1100331   .0557431    -1.97   0.049                -.0603844
     _Istateicps_25 |   .1857352   .0665411     2.79   0.005                 .0928073
     _Istateicps_31 |          0  (omitted)                                         .
     _Istateicps_32 |          0  (omitted)                                         .
     _Istateicps_33 |          0  (omitted)                                         .
     _Istateicps_34 |          0  (omitted)                                         .
     _Istateicps_35 |          0  (omitted)                                         .
     _Istateicps_36 |          0  (omitted)                                         .
     _Istateicps_37 |          0  (omitted)                                         .
     _Istateicps_40 |  -.1576362   .0572577    -2.75   0.006                -.0935172
     _Istateicps_41 |   .0876356   .0595924     1.47   0.142                 .0425575
     _Istateicps_42 |  -.2436627   .0577923    -4.22   0.000                 -.125886
     _Istateicps_43 |   .1925812    .064631     2.98   0.003                 .0928303
     _Istateicps_44 |   .1780442   .0581828     3.06   0.002                 .1306436
     _Istateicps_45 |  -.1947976   .0573614    -3.40   0.001                -.0931941
     _Istateicps_46 |   .1170214   .0611679     1.91   0.056                 .0631182
     _Istateicps_47 |  -.0157006   .0562306    -0.28   0.780                -.0092698
     _Istateicps_48 |   .0567853   .0622429     0.91   0.362                 .0231232
     _Istateicps_49 |   .5343937   .0603567     8.85   0.000                 .4823962
     _Istateicps_51 |   .0384493   .0567588     0.68   0.498                 .0248747
     _Istateicps_52 |  -.2951275   .0601104    -4.91   0.000                 -.083546
     _Istateicps_53 |   .1413956   .0606749     2.33   0.020                 .0739854
     _Istateicps_54 |  -.0343568   .0580638    -0.59   0.554                -.0198883
     _Istateicps_56 |   .0527032   .0603763     0.87   0.383                 .0234204
     _Istateicps_61 |  -.5428118   .0710616    -7.64   0.000                -.1137322
     _Istateicps_62 |          0  (omitted)                                         .
     _Istateicps_63 |  -.0656251   .0678951    -0.97   0.334                -.0258537
     _Istateicps_64 |   .1672749    .072166     2.32   0.021                  .072326
     _Istateicps_65 |  -.2146019    .095559    -2.25   0.025                -.0534605
     _Istateicps_66 |   .0703488   .0757387     0.93   0.353                 .0224375
     _Istateicps_67 |  -.2245669   .0653255    -3.44   0.001                -.0728768
     _Istateicps_68 |          0  (omitted)                                         .
     _Istateicps_71 |    .018366   .0712835     0.26   0.797                 .0083756
     _Istateicps_72 |   -.151916   .0687728    -2.21   0.027                 -.054845
     _Istateicps_73 |   .0363616   .0702835     0.52   0.605                 .0134812
     _Istateicps_98 |          0  (omitted)                                         .
              _cons |  -.2668092   .3503008    -0.76   0.446                        .
-------------------------------------------------------------------------------------
(est2 stored)

. estadd local betacoef   = string(r(PT)[1,6], "%9.3f")

added macro:
           e(betacoef) : "0.076"

.             qui: sum ww2_vol_pop40      if e(sample) == 1, d

. estadd local y_mean_round = string(r(mean), "%9.3f")

added macro:
       e(y_mean_round) : "0.634"

.        local iqr_y       = (r(p75) - r(p25))

. estadd local IQR_Y = string(`iqr_y', "%9.3f")

added macro:
              e(IQR_Y) : "0.402"

.             qui: sum iNDEXP_PC          if e(sample) == 1, d

.        local iqr_x       = (r(p75) - r(p25))

. estadd local IQR_X = string(`iqr_x', "%9.3f")

added macro:
              e(IQR_X) : "0.637"

. 
.            local IQR_Xbeta    = `iqr_x'*_b[iNDEXP_PC]

. estadd local sIQR_Xbeta   = string(`IQR_Xbeta', "%9.3f")

added macro:
         e(sIQR_Xbeta) : "0.030"

. 
.            local IQR_XbetadY  = (`IQR_Xbeta'/`iqr_y')*100

. estadd local sIQR_XbetadY = string(`IQR_XbetadY', "%9.1f") + "\%"

added macro:
       e(sIQR_XbetadY) : "7.5\%"

. 
. 
. eststo: xi:  reg ww2_awards_pop40_is iNDEXP_PC $control if sample_ols == 1 & servicecommand != 7, r beta
i.stateicpsr      _Istateicps_1-98    (naturally coded; _Istateicps_1 omitted)
note: _Istateicps_31 omitted because of collinearity
note: _Istateicps_32 omitted because of collinearity
note: _Istateicps_33 omitted because of collinearity
note: _Istateicps_34 omitted because of collinearity
note: _Istateicps_35 omitted because of collinearity
note: _Istateicps_36 omitted because of collinearity
note: _Istateicps_37 omitted because of collinearity
note: _Istateicps_62 omitted because of collinearity
note: _Istateicps_68 omitted because of collinearity
note: _Istateicps_98 omitted because of collinearity

Linear regression                               Number of obs     =      2,329
                                                F(55, 2273)       =      12.54
                                                Prob > F          =     0.0000
                                                R-squared         =     0.1858
                                                Root MSE          =     .11655

-------------------------------------------------------------------------------------
                    |               Robust
ww2_awards_pop40_is |      Coef.   Std. Err.      t    P>|t|                     Beta
--------------------+----------------------------------------------------------------
          iNDEXP_PC |   .0224353    .012969     1.73   0.084                 .0967438
         ww1_vol_sh |   .0567001   .0206198     2.75   0.006                 .1080837
ww1_awards_pop10_is |   .0358764   .0341077     1.05   0.293                 .0260863
             lpop30 |  -.0175697   .0120292    -1.46   0.144                  -.14391
           c30unemp |   .1192512   .1446239     0.82   0.410                 .0386714
          c30urban1 |   .0095073   .0062524     1.52   0.129                 .0367857
            c30farm |   .0356015   .0264233     1.35   0.178                 .0661017
            iYf_T29 |   .0154792   .0089103     1.74   0.082                 .0882522
           MEAN9628 |    .000081   .0003416     0.24   0.813                 .0122084
             c30men |  -.5979399   .2611234    -2.29   0.022                -.1056214
           c30black |  -.0504227   .0224206    -2.25   0.025                -.0787465
             c30jap |   .9391403   1.285926     0.73   0.465                 .0316447
             c30deu |   .0958424   .1331119     0.72   0.472                 .0352788
             c30ita |  -.0160179    .164022    -0.10   0.922                -.0031884
             c30vet |    .240809   .1200457     2.01   0.045                 .0668789
           lc40wage |   .0617875   .0201715     3.06   0.002                 .1709605
      iwarconpro_PC |   .0025517   .0046564     0.55   0.584                 .0126684
      _Istateicps_2 |  -.0378123   .0310207    -1.22   0.223                 -.024475
      _Istateicps_3 |  -.0103373   .0214012    -0.48   0.629                -.0057997
      _Istateicps_4 |  -.0343225   .0355168    -0.97   0.334                -.0175862
      _Istateicps_5 |   .0523741   .0504822     1.04   0.300                  .018996
      _Istateicps_6 |  -.0287632   .0363723    -0.79   0.429                -.0174228
     _Istateicps_11 |  -.0535878   .0273955    -1.96   0.051                -.0150617
     _Istateicps_12 |  -.0439979   .0229275    -1.92   0.055                -.0325913
     _Istateicps_13 |  -.0155257   .0208637    -0.74   0.457                 -.018959
     _Istateicps_14 |  -.0488293   .0224126    -2.18   0.029                -.0634946
     _Istateicps_21 |  -.0463706   .0316699    -1.46   0.143                 -.074361
     _Istateicps_22 |  -.0685787   .0293334    -2.34   0.019                -.1046788
     _Istateicps_23 |  -.0465094   .0352482    -1.32   0.187                -.0675658
     _Istateicps_24 |  -.0312327   .0291205    -1.07   0.284                -.0458958
     _Istateicps_25 |  -.0798687   .0452078    -1.77   0.077                -.1068627
     _Istateicps_31 |          0  (omitted)                                         .
     _Istateicps_32 |          0  (omitted)                                         .
     _Istateicps_33 |          0  (omitted)                                         .
     _Istateicps_34 |          0  (omitted)                                         .
     _Istateicps_35 |          0  (omitted)                                         .
     _Istateicps_36 |          0  (omitted)                                         .
     _Istateicps_37 |          0  (omitted)                                         .
     _Istateicps_40 |  -.0229854   .0233461    -0.98   0.325                -.0365132
     _Istateicps_41 |  -.0296973   .0236875    -1.25   0.210                -.0386166
     _Istateicps_42 |  -.0467803   .0232289    -2.01   0.044                -.0647162
     _Istateicps_43 |   .0009499   .0317099     0.03   0.976                 .0012261
     _Istateicps_44 |  -.0335842   .0237077    -1.42   0.157                -.0659869
     _Istateicps_45 |  -.0348613   .0233041    -1.50   0.135                -.0446591
     _Istateicps_46 |  -.0090983   .0247662    -0.37   0.713                -.0131405
     _Istateicps_47 |  -.0387923   .0221516    -1.75   0.080                -.0613279
     _Istateicps_48 |  -.0289798   .0252862    -1.15   0.252                -.0315987
     _Istateicps_49 |   .0044811   .0238381     0.19   0.851                 .0108315
     _Istateicps_51 |  -.0347781   .0232936    -1.49   0.136                -.0602471
     _Istateicps_52 |  -.0283768   .0330661    -0.86   0.391                  -.02151
     _Istateicps_53 |  -.0176927   .0253562    -0.70   0.485                -.0247894
     _Istateicps_54 |  -.0309542   .0225352    -1.37   0.170                -.0479805
     _Istateicps_56 |  -.0348911   .0241999    -1.44   0.150                -.0415177
     _Istateicps_61 |   .0046837   .0455495     0.10   0.918                 .0026277
     _Istateicps_62 |          0  (omitted)                                         .
     _Istateicps_63 |   .0022925   .0448993     0.05   0.959                 .0024184
     _Istateicps_64 |   .1114907   .0500197     2.23   0.026                 .1290815
     _Istateicps_65 |  -.0148737   .0669601    -0.22   0.824                -.0099216
     _Istateicps_66 |  -.0163989   .0329215    -0.50   0.618                -.0140053
     _Istateicps_67 |   .0022497   .0432151     0.05   0.958                 .0019549
     _Istateicps_68 |          0  (omitted)                                         .
     _Istateicps_71 |   .0697472     .05159     1.35   0.177                  .085171
     _Istateicps_72 |  -.0140163   .0395004    -0.35   0.723                -.0135497
     _Istateicps_73 |   .0191447   .0381242     0.50   0.616                 .0190062
     _Istateicps_98 |          0  (omitted)                                         .
              _cons |  -.0009659   .1738696    -0.01   0.996                        .
-------------------------------------------------------------------------------------
(est3 stored)

. estadd local betacoef   = string(r(PT)[1,6], "%9.3f")

added macro:
           e(betacoef) : "0.097"

.             qui: sum ww2_awards_pop40_is if e(sample) == 1, d

. estadd local y_mean_round = string(r(mean), "%9.3f")

added macro:
       e(y_mean_round) : "0.140"

.        local iqr_y       = (r(p75) - r(p25))

.            
. estadd local IQR_Y = string(`iqr_y', "%9.3f")

added macro:
              e(IQR_Y) : "0.130"

.             qui: sum iNDEXP_PC          if e(sample) == 1, d

.        local iqr_x       = (r(p75) - r(p25))

. estadd local IQR_X = string(`iqr_x', "%9.3f")

added macro:
              e(IQR_X) : "0.637"

. 
.            local IQR_Xbeta    = `iqr_x'*_b[iNDEXP_PC]

. estadd local sIQR_Xbeta   = string(`IQR_Xbeta', "%9.3f")

added macro:
         e(sIQR_Xbeta) : "0.014"

. 
.            local IQR_XbetadY  = (`IQR_Xbeta'/`iqr_y')*100

. estadd local sIQR_XbetadY = string(`IQR_XbetadY', "%9.1f") + "\%"

added macro:
       e(sIQR_XbetadY) : "11.0\%"

. 
. eststo: xi:  reg pc1                iNDEXP_PC $control if sample_ols == 1 & servicecommand != 7, r beta
i.stateicpsr      _Istateicps_1-98    (naturally coded; _Istateicps_1 omitted)
note: _Istateicps_31 omitted because of collinearity
note: _Istateicps_32 omitted because of collinearity
note: _Istateicps_33 omitted because of collinearity
note: _Istateicps_34 omitted because of collinearity
note: _Istateicps_35 omitted because of collinearity
note: _Istateicps_36 omitted because of collinearity
note: _Istateicps_37 omitted because of collinearity
note: _Istateicps_62 omitted because of collinearity
note: _Istateicps_68 omitted because of collinearity
note: _Istateicps_98 omitted because of collinearity

Linear regression                               Number of obs     =      2,329
                                                F(55, 2273)       =     105.15
                                                Prob > F          =     0.0000
                                                R-squared         =     0.6421
                                                Root MSE          =     .76095

-------------------------------------------------------------------------------------
                    |               Robust
                pc1 |      Coef.   Std. Err.      t    P>|t|                     Beta
--------------------+----------------------------------------------------------------
          iNDEXP_PC |   .2905177   .0733332     3.96   0.000                 .1272171
         ww1_vol_sh |   .4560195   .1143581     3.99   0.000                 .0882759
ww1_awards_pop10_is |   .5944944   .2667191     2.23   0.026                 .0438969
             lpop30 |  -.1651172   .0617808    -2.67   0.008                -.1373412
           c30unemp |   1.117586   .8242638     1.36   0.175                 .0368036
          c30urban1 |   .1773901   .0431508     4.11   0.000                 .0697001
            c30farm |  -.3136146   .1808266    -1.73   0.083                -.0591321
            iYf_T29 |   .1148773   .0509824     2.25   0.024                  .066511
           MEAN9628 |   .0050597   .0020311     2.49   0.013                 .0774608
             c30men |  -7.136619   1.548763    -4.61   0.000                -.1280175
           c30black |   -1.19932   .1488105    -8.06   0.000                -.1902053
             c30jap |   11.75079   6.774796     1.73   0.083                 .0402087
             c30deu |   .5113417   .7320231     0.70   0.485                 .0191139
             c30ita |  -.6472785   1.049279    -0.62   0.537                -.0130839
             c30vet |   3.578578   .8706198     4.11   0.000                 .1009274
           lc40wage |   1.121407   .1304695     8.60   0.000                 .3150949
      iwarconpro_PC |   .2034959   .0321466     6.33   0.000                 .1025962
      _Istateicps_2 |  -.3627044   .2123121    -1.71   0.088                -.0238411
      _Istateicps_3 |  -.1750713   .2011416    -0.87   0.384                -.0099746
      _Istateicps_4 |   .1238561   .2664606     0.46   0.642                 .0064446
      _Istateicps_5 |   -.160937   .4141036    -0.39   0.698                -.0059277
      _Istateicps_6 |   .3702565   .2540939     1.46   0.145                 .0227755
     _Istateicps_11 |  -.3055505   .1836543    -1.66   0.096                -.0087211
     _Istateicps_12 |  -.4792182   .1729917    -2.77   0.006                -.0360484
     _Istateicps_13 |  -.0658772   .1589278    -0.41   0.679                -.0081693
     _Istateicps_14 |  -.6410433   .1644978    -3.90   0.000                -.0846499
     _Istateicps_21 |  -.0317882    .203547    -0.16   0.876                -.0051767
     _Istateicps_22 |  -.3818149   .1932128    -1.98   0.048                 -.059184
     _Istateicps_23 |  -.2852551   .2232503    -1.28   0.201                -.0420826
     _Istateicps_24 |  -.3590735   .1926847    -1.86   0.063                -.0535833
     _Istateicps_25 |   .0115781   .2626636     0.04   0.965                 .0015731
     _Istateicps_31 |          0  (omitted)                                         .
     _Istateicps_32 |          0  (omitted)                                         .
     _Istateicps_33 |          0  (omitted)                                         .
     _Istateicps_34 |          0  (omitted)                                         .
     _Istateicps_35 |          0  (omitted)                                         .
     _Istateicps_36 |          0  (omitted)                                         .
     _Istateicps_37 |          0  (omitted)                                         .
     _Istateicps_40 |  -.3314276   .1828898    -1.81   0.070                -.0534649
     _Istateicps_41 |     .02769   .1820293     0.15   0.879                 .0036565
     _Istateicps_42 |  -.9414548   .1841095    -5.11   0.000                 -.132261
     _Istateicps_43 |   .2302479   .2227432     1.03   0.301                 .0301797
     _Istateicps_44 |   .0326365    .183305     0.18   0.859                 .0065119
     _Istateicps_45 |  -.7355506   .1804745    -4.08   0.000                -.0956889
     _Istateicps_46 |   .0292311   .1920808     0.15   0.879                 .0042873
     _Istateicps_47 |  -.2581259   .1761854    -1.47   0.143                -.0414406
     _Istateicps_48 |  -.4222961    .193297    -2.18   0.029                -.0467599
     _Istateicps_49 |   1.070501   .1863693     5.74   0.000                 .2627689
     _Istateicps_51 |  -.3180441   .1771939    -1.79   0.073                -.0559501
     _Istateicps_52 |  -.6701615   .2328637    -2.88   0.004                -.0515869
     _Istateicps_53 |   .2905578   .1874741     1.55   0.121                 .0413416
     _Istateicps_54 |  -.3007666   .1751095    -1.72   0.086                -.0473432
     _Istateicps_56 |  -.2712188   .1833089    -1.48   0.139                -.0327734
     _Istateicps_61 |  -.9628048   .3069335    -3.14   0.002                -.0548551
     _Istateicps_62 |          0  (omitted)                                         .
     _Istateicps_63 |    .063961   .2637903     0.24   0.808                 .0068519
     _Istateicps_64 |   1.336183   .2788972     4.79   0.000                 .1570992
     _Istateicps_65 |  -.4149235   .4208383    -0.99   0.324                -.0281068
     _Istateicps_66 |  -.1276602   .2705371    -0.47   0.637                -.0110718
     _Istateicps_67 |  -.4502307   .2696873    -1.67   0.095                -.0397304
     _Istateicps_68 |          0  (omitted)                                         .
     _Istateicps_71 |   .5152609   .2905524     1.77   0.076                 .0638961
     _Istateicps_72 |   .1998441   .2461725     0.81   0.417                 .0196187
     _Istateicps_73 |   .5189294   .2817786     1.84   0.066                 .0523163
     _Istateicps_98 |          0  (omitted)                                         .
              _cons |  -4.602729   1.197732    -3.84   0.000                        .
-------------------------------------------------------------------------------------
(est4 stored)

. estadd local betacoef   = string(r(PT)[1,6], "%9.3f")

added macro:
           e(betacoef) : "0.127"

. 
.             qui: sum pc1                if e(sample) == 1, d

. estadd local y_mean_round = string(r(mean), "%9.3f")

added macro:
       e(y_mean_round) : "-0.012"

.        local iqr_y       = (r(p75) - r(p25))

. estadd local IQR_Y = string(`iqr_y', "%9.3f")

added macro:
              e(IQR_Y) : "1.658"

.             qui: sum iNDEXP_PC          if e(sample) == 1, d

.        local iqr_x       = (r(p75) - r(p25))

. estadd local IQR_X = string(`iqr_x', "%9.3f")

added macro:
              e(IQR_X) : "0.637"

. 
.            local IQR_Xbeta    = `iqr_x'*_b[iNDEXP_PC]

. estadd local sIQR_Xbeta   = string(`IQR_Xbeta', "%9.3f")

added macro:
         e(sIQR_Xbeta) : "0.185"

. 
.            local IQR_XbetadY  = (`IQR_Xbeta'/`iqr_y')*100

. estadd local sIQR_XbetadY = string(`IQR_XbetadY', "%9.1f") + "\%"

added macro:
       e(sIQR_XbetadY) : "11.2\%"

. 
. esttab using "results/tables/Tab2_main-a.tex" ,                                                            ///
>         order(iNDEXP_PC           )                                                                                                ///
>         drop(_cons)                                                                                            ///
>         indicate("County-level controls = $control_nofe" "State FE (48) = *state*")                                ///
>         mgroups("War bonds" "Volunteers" "Medals" "PCA" , pattern(1 1 1 1 )                                    ///
>                         prefix(\multicolumn{@span}{c}{) suffix(})                                                      ///
>                         span erepeat(\cmidrule(lr){@span}) )                                                                   ///
>         replace br se  label star(* 0.10 ** 0.05 *** 0.01) obslast nomtitles  compress longtable                   ///
>     scalars("y_mean_round Mean dependent variable" "sIQR_Xbeta New Deal grant IQR $\times$ $\beta$" "sIQR_XbetadY New Deal grant IQR $\times$ 
> $\beta$ / IQR dep. var" "betacoef Beta-coefficient")                                                       ///
>         b(%9.3f) se(%9.3f) r2(%9.3f)                                                                           ///
>         nonotes nogaps title("New Deal and Patriotism: Basic Patterns (Panel A).")
(output written to results/tables/Tab2_main-a.tex)

. 
. ***************************************************************************************************
. ****              b. Panel B                                                                                       ****
. ***************************************************************************************************
. 
. estimates clear

. eststo: xi:  reg iwarbond_1944_PC    iAGRI_PF iSSA_PB iinfra_AL EW_AL    iHOLC_PH iRFC_PC $control if sample_ols == 1                      , r
i.stateicpsr      _Istateicps_1-98    (naturally coded; _Istateicps_1 omitted)
note: _Istateicps_98 omitted because of collinearity

Linear regression                               Number of obs     =      3,022
                                                F(69, 2952)       =     101.02
                                                Prob > F          =     0.0000
                                                R-squared         =     0.6913
                                                Root MSE          =     .38008

-------------------------------------------------------------------------------------
                    |               Robust
   iwarbond_1944_PC |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
           iAGRI_PF |   .1255339   .0142125     8.83   0.000     .0976666    .1534012
            iSSA_PB |   .1050814   .0507729     2.07   0.039     .0055275    .2046353
          iinfra_AL |    .057623   .0129981     4.43   0.000     .0321366    .0831093
              EW_AL |  -.0356285   .1200951    -0.30   0.767    -.2711071    .1998501
           iHOLC_PH |   .0906405   .0115444     7.85   0.000     .0680045    .1132765
            iRFC_PC |   .0204187   .0068314     2.99   0.003      .007024    .0338134
         ww1_vol_sh |  -.0202973   .0341511    -0.59   0.552    -.0872596    .0466651
ww1_awards_pop10_is |   .1706048   .0773613     2.21   0.028     .0189172    .3222924
             lpop30 |  -.0382872   .0234046    -1.64   0.102    -.0841783    .0076039
           c30unemp |  -.3646985   .2532708    -1.44   0.150    -.8613037    .1319067
          c30urban1 |   .0221926   .0206956     1.07   0.284    -.0183866    .0627718
            c30farm |  -.4374986   .1441792    -3.03   0.002    -.7202004   -.1547967
            iYf_T29 |   .0277605   .0195643     1.42   0.156    -.0106006    .0661216
           MEAN9628 |   .0010941   .0009143     1.20   0.232    -.0006986    .0028867
             c30men |  -1.075938   .6900909    -1.56   0.119    -2.429046    .2771699
           c30black |   -.267499   .0958232    -2.79   0.005     -.455386    -.079612
             c30jap |    4.72583   1.955294     2.42   0.016     .8919521    8.559707
             c30deu |   .7322721   .2043548     3.58   0.000     .3315797    1.132964
             c30ita |   .2654517   .4745262     0.56   0.576     -.664984    1.195887
             c30vet |  -.1121537   .7887507    -0.14   0.887    -1.658711    1.434403
           lc40wage |   .3902191   .0555612     7.02   0.000     .2812765    .4991616
      iwarconpro_PC |   .2809411   .0222998    12.60   0.000     .2372163    .3246659
      _Istateicps_2 |  -.0248208   .1368182    -0.18   0.856    -.2930895    .2434478
      _Istateicps_3 |   -.181523   .1286913    -1.41   0.158    -.4338567    .0708108
      _Istateicps_4 |   .1170015   .1763113     0.66   0.507    -.2287041    .4627071
      _Istateicps_5 |  -.2826817   .3678827    -0.77   0.442    -1.004014    .4386509
      _Istateicps_6 |  -.0493597   .1282497    -0.38   0.700    -.3008276    .2021082
     _Istateicps_11 |   .2369005   .1464294     1.62   0.106    -.0502137    .5240146
     _Istateicps_12 |  -.0665443   .1163753    -0.57   0.567    -.2947292    .1616407
     _Istateicps_13 |   .0305803   .1008768     0.30   0.762    -.1672157    .2283764
     _Istateicps_14 |   .1555212   .1008484     1.54   0.123     -.042219    .3532615
     _Istateicps_21 |   .0720493   .1078613     0.67   0.504    -.1394416    .2835403
     _Istateicps_22 |    .038182   .1082847     0.35   0.724    -.1741392    .2505032
     _Istateicps_23 |  -.0513426   .1089132    -0.47   0.637    -.2648961     .162211
     _Istateicps_24 |  -.1053683   .1127627    -0.93   0.350    -.3264699    .1157332
     _Istateicps_25 |  -.0595726   .1180873    -0.50   0.614    -.2911143    .1719691
     _Istateicps_31 |   .4614346   .1107201     4.17   0.000     .2443383     .678531
     _Istateicps_32 |   .4046152   .1196072     3.38   0.001     .1700933    .6391372
     _Istateicps_33 |   .1965961    .124388     1.58   0.114       -.0473    .4404922
     _Istateicps_34 |   -.000824   .1082142    -0.01   0.994    -.2130069    .2113589
     _Istateicps_35 |   .3533847    .116008     3.05   0.002       .12592    .5808494
     _Istateicps_36 |   .5014135   .1347427     3.72   0.000     .2372143    .7656126
     _Istateicps_37 |   .2400154   .1238096     1.94   0.053    -.0027466    .4827773
     _Istateicps_40 |   .3775629   .2046442     1.84   0.065    -.0236969    .7788228
     _Istateicps_41 |   .1425664   .1458875     0.98   0.329    -.1434852    .4286179
     _Istateicps_42 |  -.2808073   .1429479    -1.96   0.050     -.561095   -.0005196
     _Istateicps_43 |   .0225701   .1312657     0.17   0.863    -.2348114    .2799516
     _Istateicps_44 |  -.0725198   .1522713    -0.48   0.634    -.3710885    .2260489
     _Istateicps_45 |  -.1912105   .1268887    -1.51   0.132    -.4400097    .0575887
     _Istateicps_46 |   .0969428    .163286     0.59   0.553    -.2232232    .4171088
     _Istateicps_47 |   .0367379   .1430891     0.26   0.797    -.2438266    .3173025
     _Istateicps_48 |  -.1990805   .1621758    -1.23   0.220    -.5170696    .1189086
     _Istateicps_49 |   .0645931   .1126813     0.57   0.567    -.1563489     .285535
     _Istateicps_51 |  -.1459769   .1227334    -1.19   0.234    -.3866287    .0946748
     _Istateicps_52 |  -.1145793    .139638    -0.82   0.412     -.388377    .1592184
     _Istateicps_53 |  -.0328742   .1135613    -0.29   0.772    -.2555414    .1897931
     _Istateicps_54 |    -.00519   .1372057    -0.04   0.970    -.2742184    .2638385
     _Istateicps_56 |   -.035692   .1182906    -0.30   0.763    -.2676324    .1962484
     _Istateicps_61 |  -.1188999   .1447878    -0.82   0.412    -.4027952    .1649955
     _Istateicps_62 |  -.1159507   .1175094    -0.99   0.324    -.3463594    .1144579
     _Istateicps_63 |   .0054319   .1309786     0.04   0.967    -.2513868    .2622506
     _Istateicps_64 |   .4211196   .1247075     3.38   0.001     .1765972     .665642
     _Istateicps_65 |  -.0821553   .1687372    -0.49   0.626    -.4130098    .2486993
     _Istateicps_66 |  -.2174886   .1453623    -1.50   0.135    -.5025104    .0675331
     _Istateicps_67 |  -.2639983    .127073    -2.08   0.038     -.513159   -.0148377
     _Istateicps_68 |   .1169437   .1246369     0.94   0.348    -.1274403    .3613277
     _Istateicps_71 |   .0368372   .1211609     0.30   0.761    -.2007312    .2744056
     _Istateicps_72 |   .5190004   .1212057     4.28   0.000     .2813441    .7566566
     _Istateicps_73 |   .3496281    .151357     2.31   0.021     .0528522     .646404
     _Istateicps_98 |          0  (omitted)
              _cons |   .8780998   .7852569     1.12   0.264    -.6616068    2.417806
-------------------------------------------------------------------------------------
(est1 stored)

.             qui: sum iwarbond_1944_PC   if e(sample) == 1

. estadd local y_mean_round = string(r(mean), "%9.3f")

added macro:
       e(y_mean_round) : "4.658"

. eststo: xi:  reg ww2_vol_pop40       iAGRI_PF iSSA_PB iinfra_AL EW_AL    iHOLC_PH iRFC_PC $control if sample_ols == 1 & servicecommand != 7, r
i.stateicpsr      _Istateicps_1-98    (naturally coded; _Istateicps_1 omitted)
note: _Istateicps_31 omitted because of collinearity
note: _Istateicps_32 omitted because of collinearity
note: _Istateicps_33 omitted because of collinearity
note: _Istateicps_34 omitted because of collinearity
note: _Istateicps_35 omitted because of collinearity
note: _Istateicps_36 omitted because of collinearity
note: _Istateicps_37 omitted because of collinearity
note: _Istateicps_62 omitted because of collinearity
note: _Istateicps_68 omitted because of collinearity
note: _Istateicps_98 omitted because of collinearity

Linear regression                               Number of obs     =      2,329
                                                F(60, 2268)       =      70.09
                                                Prob > F          =     0.0000
                                                R-squared         =     0.6304
                                                Root MSE          =      .2105

-------------------------------------------------------------------------------------
                    |               Robust
      ww2_vol_pop40 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
           iAGRI_PF |   .0304224   .0074215     4.10   0.000     .0158688    .0449761
            iSSA_PB |    .029447   .0150759     1.95   0.051     -.000117     .059011
          iinfra_AL |  -.0069517   .0044457    -1.56   0.118    -.0156698    .0017664
              EW_AL |    .029517    .076611     0.39   0.700     -.120718    .1797521
           iHOLC_PH |   .0345502   .0066241     5.22   0.000     .0215602    .0475402
            iRFC_PC |  -.0011977   .0042612    -0.28   0.779     -.009554    .0071586
         ww1_vol_sh |    .104887   .0265989     3.94   0.000     .0527263    .1570478
ww1_awards_pop10_is |   .1118636   .0963528     1.16   0.246    -.0770852    .3008125
             lpop30 |  -.0221518   .0109301    -2.03   0.043    -.0435859   -.0007178
           c30unemp |   .5654461    .199575     2.83   0.005     .1740775    .9568148
          c30urban1 |  -.0011914   .0129168    -0.09   0.927    -.0265213    .0241385
            c30farm |  -.0581636   .0542946    -1.07   0.284    -.1646358    .0483086
            iYf_T29 |  -.0373318   .0117059    -3.19   0.001    -.0602871   -.0143765
           MEAN9628 |  -.0007018   .0005307    -1.32   0.186    -.0017426     .000339
             c30men |    -.87069   .5168996    -1.68   0.092    -1.884336    .1429555
           c30black |  -.4131071   .0412229   -10.02   0.000    -.4939457   -.3322685
             c30jap |   .4228907     1.2721     0.33   0.740    -2.071711    2.917493
             c30deu |  -.6166827   .1533718    -4.02   0.000    -.9174463   -.3159191
             c30ita |  -.2243205   .2348738    -0.96   0.340    -.6849105    .2362696
             c30vet |    1.01298   .3106782     3.26   0.001      .403737    1.622223
           lc40wage |   .2059947    .034531     5.97   0.000      .138279    .2737104
      iwarconpro_PC |   -.034218   .0076849    -4.45   0.000    -.0492882   -.0191478
      _Istateicps_2 |   .0180089   .0567387     0.32   0.751    -.0932563    .1292741
      _Istateicps_3 |   .0284389   .0544422     0.52   0.601    -.0783228    .1352005
      _Istateicps_4 |   .2569161   .0805067     3.19   0.001     .0990417    .4147905
      _Istateicps_5 |  -.0065722   .0579732    -0.11   0.910    -.1202582    .1071138
      _Istateicps_6 |   .2875111   .0762592     3.77   0.000      .137966    .4370562
     _Istateicps_11 |  -.1765995   .0583322    -3.03   0.002    -.2909895   -.0622095
     _Istateicps_12 |  -.0996213   .0499435    -1.99   0.046     -.197561   -.0016817
     _Istateicps_13 |    .049757   .0499116     1.00   0.319    -.0481201    .1476341
     _Istateicps_14 |  -.1876922    .048138    -3.90   0.000    -.2820913   -.0932931
     _Istateicps_21 |  -.0031855   .0528198    -0.06   0.952    -.1067657    .1003946
     _Istateicps_22 |  -.1090453   .0510877    -2.13   0.033    -.2092288   -.0088618
     _Istateicps_23 |  -.0657129    .057411    -1.14   0.252    -.1782965    .0468708
     _Istateicps_24 |  -.1362186   .0519052    -2.62   0.009    -.2380052   -.0344321
     _Istateicps_25 |   .1382551   .0623805     2.22   0.027     .0159263     .260584
     _Istateicps_31 |          0  (omitted)
     _Istateicps_32 |          0  (omitted)
     _Istateicps_33 |          0  (omitted)
     _Istateicps_34 |          0  (omitted)
     _Istateicps_35 |          0  (omitted)
     _Istateicps_36 |          0  (omitted)
     _Istateicps_37 |          0  (omitted)
     _Istateicps_40 |  -.0756498   .0691132    -1.09   0.274    -.2111815    .0598818
     _Istateicps_41 |   .1072229   .0587246     1.83   0.068    -.0079368    .2223825
     _Istateicps_42 |   -.235946   .0546361    -4.32   0.000    -.3430879    -.128804
     _Istateicps_43 |   .1856626   .0604391     3.07   0.002     .0671408    .3041844
     _Istateicps_44 |   .1754124   .0582291     3.01   0.003     .0612245    .2896003
     _Istateicps_45 |  -.1916801   .0531357    -3.61   0.000    -.2958798   -.0874803
     _Istateicps_46 |   .1598956   .0607727     2.63   0.009     .0407197    .2790715
     _Istateicps_47 |   .0064216   .0556108     0.12   0.908    -.1026317    .1154749
     _Istateicps_48 |   .0941707   .0611898     1.54   0.124    -.0258231    .2141646
     _Istateicps_49 |    .495914   .0556973     8.90   0.000     .3866911     .605137
     _Istateicps_51 |   .0577689   .0538597     1.07   0.284    -.0478505    .1633882
     _Istateicps_52 |  -.3034048   .0545473    -5.56   0.000    -.4103727   -.1964369
     _Istateicps_53 |   .0688139   .0585188     1.18   0.240     -.045942    .1835698
     _Istateicps_54 |  -.0135535   .0575702    -0.24   0.814    -.1264494    .0993423
     _Istateicps_56 |   .0749189   .0581606     1.29   0.198    -.0391347    .1889726
     _Istateicps_61 |  -.5321214   .0654002    -8.14   0.000    -.6603719   -.4038709
     _Istateicps_62 |          0  (omitted)
     _Istateicps_63 |  -.1271466   .0636277    -2.00   0.046    -.2519213    -.002372
     _Istateicps_64 |   .0971533   .0660315     1.47   0.141    -.0323351    .2266416
     _Istateicps_65 |  -.2082371   .0888214    -2.34   0.019    -.3824169   -.0340573
     _Istateicps_66 |   .0848446   .0688331     1.23   0.218    -.0501379    .2198271
     _Istateicps_67 |   -.272057   .0628628    -4.33   0.000    -.3953317   -.1487824
     _Istateicps_68 |          0  (omitted)
     _Istateicps_71 |  -.0260394   .0703169    -0.37   0.711    -.1639315    .1118527
     _Istateicps_72 |  -.1755773   .0637355    -2.75   0.006    -.3005632   -.0505913
     _Istateicps_73 |   .0043172     .06442     0.07   0.947    -.1220111    .1306454
     _Istateicps_98 |          0  (omitted)
              _cons |   -.410328   .3689215    -1.11   0.266    -1.133787    .3131309
-------------------------------------------------------------------------------------
(est2 stored)

.             qui: sum ww2_vol_pop40      if e(sample) == 1

. estadd local y_mean_round = string(r(mean), "%9.3f")

added macro:
       e(y_mean_round) : "0.634"

. eststo: xi:  reg ww2_awards_pop40_is iAGRI_PF iSSA_PB iinfra_AL EW_AL    iHOLC_PH iRFC_PC $control if sample_ols == 1 & servicecommand != 7, r
i.stateicpsr      _Istateicps_1-98    (naturally coded; _Istateicps_1 omitted)
note: _Istateicps_31 omitted because of collinearity
note: _Istateicps_32 omitted because of collinearity
note: _Istateicps_33 omitted because of collinearity
note: _Istateicps_34 omitted because of collinearity
note: _Istateicps_35 omitted because of collinearity
note: _Istateicps_36 omitted because of collinearity
note: _Istateicps_37 omitted because of collinearity
note: _Istateicps_62 omitted because of collinearity
note: _Istateicps_68 omitted because of collinearity
note: _Istateicps_98 omitted because of collinearity

Linear regression                               Number of obs     =      2,329
                                                F(60, 2268)       =      11.81
                                                Prob > F          =     0.0000
                                                R-squared         =     0.1937
                                                Root MSE          =     .11612

-------------------------------------------------------------------------------------
                    |               Robust
ww2_awards_pop40_is |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
           iAGRI_PF |   .0108331   .0039901     2.71   0.007     .0030085    .0186578
            iSSA_PB |   .0091705   .0070694     1.30   0.195    -.0046928    .0230338
          iinfra_AL |   .0064884   .0034451     1.88   0.060    -.0002675    .0132442
              EW_AL |   .0057755   .0493499     0.12   0.907    -.0910003    .1025512
           iHOLC_PH |   .0099533   .0039843     2.50   0.013     .0021401    .0177665
            iRFC_PC |  -.0022119   .0027733    -0.80   0.425    -.0076504    .0032266
         ww1_vol_sh |   .0544753   .0207392     2.63   0.009     .0138055    .0951452
ww1_awards_pop10_is |   .0314483   .0341132     0.92   0.357    -.0354482    .0983447
             lpop30 |  -.0171824   .0121532    -1.41   0.158     -.041015    .0066503
           c30unemp |   .1507619   .1579277     0.95   0.340     -.158936    .4604599
          c30urban1 |   .0030656   .0064158     0.48   0.633    -.0095159    .0156472
            c30farm |   .0320545   .0264019     1.21   0.225    -.0197199    .0838289
            iYf_T29 |   .0103775   .0096027     1.08   0.280    -.0084534    .0292085
           MEAN9628 |  -.0001791   .0003362    -0.53   0.594    -.0008383    .0004801
             c30men |  -.5124318   .2729317    -1.88   0.061    -1.047654    .0227902
           c30black |   -.049341   .0219526    -2.25   0.025    -.0923903   -.0062918
             c30jap |   .8099383    1.31834     0.61   0.539    -1.775341    3.395217
             c30deu |   .0701456   .1201067     0.58   0.559    -.1653848    .3056761
             c30ita |   .0292398   .1613096     0.18   0.856    -.2870901    .3455696
             c30vet |   .2400354   .1082788     2.22   0.027     .0276996    .4523713
           lc40wage |   .0479974   .0184441     2.60   0.009     .0118284    .0841665
      iwarconpro_PC |    .004513   .0045254     1.00   0.319    -.0043613    .0133873
      _Istateicps_2 |  -.0209562   .0324412    -0.65   0.518    -.0845737    .0426613
      _Istateicps_3 |  -.0039797   .0216113    -0.18   0.854    -.0463598    .0384003
      _Istateicps_4 |  -.0165477   .0383508    -0.43   0.666     -.091754    .0586586
      _Istateicps_5 |   .0545871   .0538801     1.01   0.311    -.0510724    .1602465
      _Istateicps_6 |  -.0257876   .0378206    -0.68   0.495    -.0999541    .0483789
     _Istateicps_11 |  -.0526415   .0277965    -1.89   0.058    -.1071508    .0018678
     _Istateicps_12 |  -.0328481   .0220468    -1.49   0.136    -.0760822    .0103859
     _Istateicps_13 |  -.0035108   .0211023    -0.17   0.868    -.0448926    .0378711
     _Istateicps_14 |  -.0217785   .0211541    -1.03   0.303    -.0632619    .0197049
     _Istateicps_21 |  -.0439752   .0269456    -1.63   0.103    -.0968158    .0088653
     _Istateicps_22 |  -.0638696   .0263685    -2.42   0.016    -.1155785   -.0121606
     _Istateicps_23 |  -.0408644   .0307903    -1.33   0.185    -.1012445    .0195156
     _Istateicps_24 |  -.0299064   .0269254    -1.11   0.267    -.0827074    .0228946
     _Istateicps_25 |  -.0817802   .0394531    -2.07   0.038    -.1591481   -.0044124
     _Istateicps_31 |          0  (omitted)
     _Istateicps_32 |          0  (omitted)
     _Istateicps_33 |          0  (omitted)
     _Istateicps_34 |          0  (omitted)
     _Istateicps_35 |          0  (omitted)
     _Istateicps_36 |          0  (omitted)
     _Istateicps_37 |          0  (omitted)
     _Istateicps_40 |   .0050742   .0335706     0.15   0.880    -.0607581    .0709064
     _Istateicps_41 |  -.0159586   .0273951    -0.58   0.560    -.0696806    .0377635
     _Istateicps_42 |  -.0314911   .0254642    -1.24   0.216    -.0814267    .0184446
     _Istateicps_43 |   .0113958   .0312761     0.36   0.716    -.0499369    .0727285
     _Istateicps_44 |   -.027923   .0272374    -1.03   0.305    -.0813358    .0254898
     _Istateicps_45 |  -.0198301   .0251709    -0.79   0.431    -.0691905    .0295302
     _Istateicps_46 |   .0152721   .0296521     0.52   0.607     -.042876    .0734203
     _Istateicps_47 |  -.0298913   .0255827    -1.17   0.243    -.0800592    .0202766
     _Istateicps_48 |  -.0104346   .0300966    -0.35   0.729    -.0694544    .0485852
     _Istateicps_49 |  -.0014039   .0238287    -0.06   0.953    -.0481323    .0453245
     _Istateicps_51 |  -.0166342   .0244039    -0.68   0.496    -.0644906    .0312221
     _Istateicps_52 |  -.0273941   .0334078    -0.82   0.412    -.0929072     .038119
     _Istateicps_53 |  -.0306614   .0265682    -1.15   0.249    -.0827618     .021439
     _Istateicps_54 |  -.0152357    .025333    -0.60   0.548    -.0649141    .0344427
     _Istateicps_56 |  -.0084792   .0255042    -0.33   0.740    -.0584932    .0415348
     _Istateicps_61 |   .0060158    .044039     0.14   0.891    -.0803451    .0923766
     _Istateicps_62 |          0  (omitted)
     _Istateicps_63 |  -.0080286   .0417593    -0.19   0.848     -.089919    .0738618
     _Istateicps_64 |   .1023384   .0441614     2.32   0.021     .0157374    .1889393
     _Istateicps_65 |  -.0087957   .0595979    -0.15   0.883    -.1256678    .1080765
     _Istateicps_66 |  -.0087652    .031456    -0.28   0.781    -.0704507    .0529203
     _Istateicps_67 |  -.0077164   .0411847    -0.19   0.851    -.0884801    .0730473
     _Istateicps_68 |          0  (omitted)
     _Istateicps_71 |   .0605903   .0551571     1.10   0.272    -.0475734    .1687541
     _Istateicps_72 |  -.0117161   .0376439    -0.31   0.756    -.0855362    .0621039
     _Istateicps_73 |   .0217024   .0360232     0.60   0.547    -.0489394    .0923442
     _Istateicps_98 |          0  (omitted)
              _cons |   .0003774   .2052617     0.00   0.999     -.402143    .4028978
-------------------------------------------------------------------------------------
(est3 stored)

.             qui: sum ww2_awards_pop40_is if e(sample) == 1

. estadd local y_mean_round = string(r(mean), "%9.3f")

added macro:
       e(y_mean_round) : "0.140"

. eststo: xi:  reg pc1                 iAGRI_PF iSSA_PB iinfra_AL EW_AL    iHOLC_PH iRFC_PC $control if sample_ols == 1 & servicecommand != 7, r
i.stateicpsr      _Istateicps_1-98    (naturally coded; _Istateicps_1 omitted)
note: _Istateicps_31 omitted because of collinearity
note: _Istateicps_32 omitted because of collinearity
note: _Istateicps_33 omitted because of collinearity
note: _Istateicps_34 omitted because of collinearity
note: _Istateicps_35 omitted because of collinearity
note: _Istateicps_36 omitted because of collinearity
note: _Istateicps_37 omitted because of collinearity
note: _Istateicps_62 omitted because of collinearity
note: _Istateicps_68 omitted because of collinearity
note: _Istateicps_98 omitted because of collinearity

Linear regression                               Number of obs     =      2,329
                                                F(60, 2268)       =     101.70
                                                Prob > F          =     0.0000
                                                R-squared         =     0.6664
                                                Root MSE          =     .73549

-------------------------------------------------------------------------------------
                    |               Robust
                pc1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
           iAGRI_PF |   .1879181   .0261458     7.19   0.000     .1366459    .2391902
            iSSA_PB |   .1376385   .0473361     2.91   0.004      .044812     .230465
          iinfra_AL |   .0504551   .0198326     2.54   0.011     .0115631    .0893471
              EW_AL |   .0351057   .2996198     0.12   0.907    -.5524518    .6226632
           iHOLC_PH |    .167161   .0260024     6.43   0.000     .1161699    .2181521
            iRFC_PC |   .0094373   .0164076     0.58   0.565    -.0227382    .0416129
         ww1_vol_sh |   .4204961   .1159379     3.63   0.000     .1931406    .6478516
ww1_awards_pop10_is |   .4986933   .2546567     1.96   0.050    -.0006912    .9980778
             lpop30 |  -.1778627   .0633636    -2.81   0.005    -.3021193    -.053606
           c30unemp |   1.514913   .8877337     1.71   0.088     -.225942    3.255768
          c30urban1 |   .0697799   .0427555     1.63   0.103    -.0140641     .153624
            c30farm |  -.2720525   .1789074    -1.52   0.128    -.6228917    .0787867
            iYf_T29 |   .0129911   .0549356     0.24   0.813    -.0947381    .1207204
           MEAN9628 |   .0003874   .0019585     0.20   0.843    -.0034532    .0042281
             c30men |   -5.40404   1.568313    -3.45   0.001    -8.479518   -2.328563
           c30black |   -1.14983   .1499295    -7.67   0.000    -1.443843   -.8558163
             c30jap |   9.781422   7.034764     1.39   0.165    -4.013823    23.57667
             c30deu |   .1769601   .6640829     0.27   0.790    -1.125313    1.479234
             c30ita |  -.0420831   1.025318    -0.04   0.967    -2.052743    1.968576
             c30vet |   3.380947   .7841292     4.31   0.000     1.843261    4.918633
           lc40wage |    .942287    .125016     7.54   0.000     .6971293    1.187445
      iwarconpro_PC |   .2332027   .0312507     7.46   0.000     .1719197    .2944857
      _Istateicps_2 |  -.1021782   .2047465    -0.50   0.618    -.5036883    .2993319
      _Istateicps_3 |  -.0880236   .1952246    -0.45   0.652    -.4708611     .294814
      _Istateicps_4 |    .421056   .2795858     1.51   0.132    -.1272146    .9693266
      _Istateicps_5 |  -.0756511   .4632952    -0.16   0.870    -.9841779    .8328757
      _Istateicps_6 |   .3476426   .2570402     1.35   0.176    -.1564159    .8517011
     _Istateicps_11 |  -.2544167    .186846    -1.36   0.173    -.6208237    .1119903
     _Istateicps_12 |  -.3701948   .1652036    -2.24   0.025    -.6941608   -.0462288
     _Istateicps_13 |   .0965571   .1595195     0.61   0.545    -.2162624    .4093766
     _Istateicps_14 |  -.2747081   .1580746    -1.74   0.082    -.5846939    .0352778
     _Istateicps_21 |   -.090142   .1822842    -0.49   0.621    -.4476032    .2673192
     _Istateicps_22 |  -.4183516   .1808272    -2.31   0.021    -.7729557   -.0637475
     _Istateicps_23 |  -.2953574   .2045938    -1.44   0.149     -.696568    .1058532
     _Istateicps_24 |  -.4090297   .1841374    -2.22   0.026     -.770125   -.0479344
     _Istateicps_25 |  -.1400885    .239552    -0.58   0.559    -.6098525    .3296755
     _Istateicps_31 |          0  (omitted)
     _Istateicps_32 |          0  (omitted)
     _Istateicps_33 |          0  (omitted)
     _Istateicps_34 |          0  (omitted)
     _Istateicps_35 |          0  (omitted)
     _Istateicps_36 |          0  (omitted)
     _Istateicps_37 |          0  (omitted)
     _Istateicps_40 |   .1039744   .2324263     0.45   0.655    -.3518161    .5597649
     _Istateicps_41 |   .2017329   .1949446     1.03   0.301    -.1805555    .5840212
     _Istateicps_42 |  -.8072379   .1890112    -4.27   0.000    -1.177891   -.4365849
     _Istateicps_43 |   .3550872    .215816     1.65   0.100    -.0681302    .7783047
     _Istateicps_44 |   .0693568   .1965251     0.35   0.724     -.316031    .4547445
     _Istateicps_45 |  -.6047411   .1827527    -3.31   0.001     -.963121   -.2463611
     _Istateicps_46 |   .3336885   .2073704     1.61   0.108    -.0729669     .740344
     _Istateicps_47 |  -.1176605   .1902855    -0.62   0.536    -.4908123    .2554912
     _Istateicps_48 |  -.1386447   .2100387    -0.66   0.509    -.5505327    .2732433
     _Istateicps_49 |   .9148999   .1804562     5.07   0.000     .5610234    1.268776
     _Istateicps_51 |  -.1032152   .1794847    -0.58   0.565    -.4551865    .2487561
     _Istateicps_52 |  -.7053236   .2296791    -3.07   0.002    -1.155727   -.2549204
     _Istateicps_53 |   .0374856    .189428     0.20   0.843    -.3339846    .4089559
     _Istateicps_54 |  -.1173089    .186364    -0.63   0.529    -.4827707    .2481529
     _Istateicps_56 |   .0354448   .1893524     0.19   0.852    -.3358773    .4067668
     _Istateicps_61 |  -.9283373    .288949    -3.21   0.001    -1.494969   -.3617053
     _Istateicps_62 |          0  (omitted)
     _Istateicps_63 |  -.1857742   .2479332    -0.75   0.454    -.6719738    .3004253
     _Istateicps_64 |   1.041502   .2456029     4.24   0.000      .559872    1.523132
     _Istateicps_65 |  -.4230489   .3664968    -1.15   0.248    -1.141753    .2956552
     _Istateicps_66 |  -.0713089   .2447182    -0.29   0.771     -.551204    .4085861
     _Istateicps_67 |  -.6569037   .2537122    -2.59   0.010    -1.154436   -.1593713
     _Istateicps_68 |          0  (omitted)
     _Istateicps_71 |   .3004678     .30631     0.98   0.327    -.3002093    .9011449
     _Istateicps_72 |   .1100348   .2335577     0.47   0.638    -.3479743    .5680438
     _Istateicps_73 |   .4517452   .2621411     1.72   0.085    -.0623163    .9658067
     _Istateicps_98 |          0  (omitted)
              _cons |  -4.923569   1.306218    -3.77   0.000    -7.485076   -2.362062
-------------------------------------------------------------------------------------
(est4 stored)

.             qui: sum pc1                if e(sample) == 1

. estadd local y_mean_round = string(r(mean), "%9.3f")

added macro:
       e(y_mean_round) : "-0.012"

. 
. esttab using "results/tables/Tab2_main-b.tex" ,                                                                            ///
>         order(iAGRI_PF iSSA_PB iinfra_AL EW_AL    iHOLC_PH iRFC_PC )                                                           ///
>         indicate("County controls = $control_nofe" "State FE (48) = *state*")                                          ///
>         drop(_cons)                                                                                            ///
>         mgroups("War bonds" "Volunteers" "Medals" "PCA" , pattern(1 1 1 1 )                                    ///
>                         prefix(\multicolumn{@span}{c}{) suffix(})                                                      ///
>                         span erepeat(\cmidrule(lr){@span}) )                                                                   ///
>         replace br se  label star(* 0.10 ** 0.05 *** 0.01) obslast nomtitles  compress longtable                   ///
>     scalars("y_mean_round Mean dependent variable" )                                                       ///
>         b(%9.3f) se(%9.3f) r2(%9.3f)                                                                           ///
>         nonotes nogaps title("New Deal and Patriotism: Basic Patterns (Panel B).")
(output written to results/tables/Tab2_main-b.tex)

.         
. ***************************************************************************************************
. ****         Tab 3. New Deal Support and Patriotism: Individual-Level Results                  ****
. ****              a. Panel D                                                                                       ****
. ***************************************************************************************************
. 
. use "tmp/asn", clear

. 
. qui reghdfe vol  iAAA_PF_farmer iAAA_PF_farmhand                                   farmer farmhand $controls_asn, absorb(countyn)

. gen insample = e(sample) == 1

. 
. estimates clear

. eststo: xi: reghdfe vol  iAAA_PF_farmer iAAA_PF_farmhand i.C40AGE                           farmer farmhand                                   
>                 if insample == 1, cluster(countyn)  absorb(countyn)
i.C40AGE          _IC40AGE_11-40      (naturally coded; _IC40AGE_11 omitted)
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =    463,248
Absorbing 1 HDFE group                            F(  33,   2314) =     104.78
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.1031
                                                  Adj R-squared   =     0.0985
                                                  Within R-sq.    =     0.0382
Number of clusters (countyn) =      2,315         Root MSE        =     0.3365

                                (Std. Err. adjusted for 2,315 clusters in countyn)
----------------------------------------------------------------------------------
                 |               Robust
       volunteer |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------+----------------------------------------------------------------
  iAAA_PF_farmer |   20.78179    4.67442     4.45   0.000      11.6153    29.94827
iAAA_PF_farmhand |   -11.0915   3.569014    -3.11   0.002     -18.0903   -4.092701
     _IC40AGE_12 |   .0478733   .0534244     0.90   0.370    -.0568914     .152638
     _IC40AGE_13 |  -.0236381   .0508876    -0.46   0.642    -.1234282     .076152
     _IC40AGE_14 |    .000176   .0508875     0.00   0.997    -.0996139    .0999659
     _IC40AGE_15 |   -.032386    .050737    -0.64   0.523    -.1318807    .0671086
     _IC40AGE_16 |   .2359437   .0512386     4.60   0.000     .1354653    .3364221
     _IC40AGE_17 |   .1682434     .05074     3.32   0.001     .0687428     .267744
     _IC40AGE_18 |   .1524725   .0504715     3.02   0.003     .0534984    .2514465
     _IC40AGE_19 |     .09739   .0503146     1.94   0.053    -.0012764    .1960564
     _IC40AGE_20 |   .0954181   .0503756     1.89   0.058    -.0033679    .1942041
     _IC40AGE_21 |   .0729751   .0502997     1.45   0.147     -.025662    .1716123
     _IC40AGE_22 |   .0604274   .0502902     1.20   0.230    -.0381912     .159046
     _IC40AGE_23 |    .047568   .0502651     0.95   0.344    -.0510014    .1461374
     _IC40AGE_24 |   .0399904   .0502776     0.80   0.426    -.0586034    .1385842
     _IC40AGE_25 |   .0328283   .0503296     0.65   0.514    -.0658676    .1315242
     _IC40AGE_26 |   .0114132   .0503065     0.23   0.821    -.0872373    .1100637
     _IC40AGE_27 |   .0017157   .0502706     0.03   0.973    -.0968643    .1002958
     _IC40AGE_28 |  -.0041698     .05032    -0.08   0.934    -.1028469    .0945073
     _IC40AGE_29 |  -.0138787   .0503114    -0.28   0.783    -.1125389    .0847814
     _IC40AGE_30 |  -.0141233   .0503079    -0.28   0.779    -.1127766      .08453
     _IC40AGE_31 |  -.0151635   .0504438    -0.30   0.764    -.1140833    .0837562
     _IC40AGE_32 |  -.0209709    .050364    -0.42   0.677    -.1197342    .0777923
     _IC40AGE_33 |  -.0339248   .0503618    -0.67   0.501    -.1326839    .0648342
     _IC40AGE_34 |  -.0428434   .0504352    -0.85   0.396    -.1417464    .0560596
     _IC40AGE_35 |  -.0551259   .0503277    -1.10   0.273     -.153818    .0435661
     _IC40AGE_36 |  -.0459645   .0503514    -0.91   0.361    -.1447031    .0527742
     _IC40AGE_37 |  -.0380677   .0504571    -0.75   0.451    -.1370135    .0608782
     _IC40AGE_38 |  -.0434649   .0503516    -0.86   0.388    -.1422038     .055274
     _IC40AGE_39 |  -.0502085   .0504549    -1.00   0.320      -.14915     .048733
     _IC40AGE_40 |  -.0568269   .0503317    -1.13   0.259    -.1555268     .041873
          farmer |  -.2257089   .0277228    -8.14   0.000    -.2800731   -.1713448
        farmhand |  -.0107054   .0217911    -0.49   0.623    -.0534375    .0320267
           _cons |   .1562849   .0504014     3.10   0.002     .0574483    .2551216
----------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     countyn |      2315        2315           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est1 stored)

.        qui:    sum  vol if e(sample) == 1

.         estadd local y_mean_round = string(r(mean), "%9.3f")

added macro:
       e(y_mean_round) : "0.147"

.         estadd local sample       = "Army"

added macro:
             e(sample) : "Army"

.         estadd local fe           = "County"

added macro:
                 e(fe) : "County"

. 
. eststo: xi: reghdfe vol  iAAA_PF_farmer iAAA_PF_farmhand                                   farmer farmhand $controls_asn                      
>    if insample == 1, cluster(countyn) absorb(countyn)
i.C40AGE          _IC40AGE_11-40      (naturally coded; _IC40AGE_11 omitted)
(MWFE estimator converged in 1 iterations)
note: C40SCHOOL_C omitted because of collinearity

HDFE Linear regression                            Number of obs   =    463,248
Absorbing 1 HDFE group                            F(  41,   2314) =     199.73
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.1426
                                                  Adj R-squared   =     0.1383
                                                  Within R-sq.    =     0.0806
Number of clusters (countyn) =      2,315         Root MSE        =     0.3290

                                (Std. Err. adjusted for 2,315 clusters in countyn)
----------------------------------------------------------------------------------
                 |               Robust
       volunteer |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------+----------------------------------------------------------------
  iAAA_PF_farmer |   20.59674   4.498435     4.58   0.000     11.77536    29.41813
iAAA_PF_farmhand |  -9.710665   3.524256    -2.76   0.006    -16.62169   -2.799635
          farmer |  -.1828161   .0270585    -6.76   0.000    -.2358777   -.1297546
        farmhand |   .0263291   .0218702     1.20   0.229    -.0165582    .0692164
               h |   .3787362   .0476633     7.95   0.000     .2852689    .4722035
               w |  -.0026902   .0005874    -4.58   0.000    -.0038422   -.0015383
             bmi |   .0030478    .001741     1.75   0.080    -.0003663    .0064619
     C40NONWHITE |  -.1155048   .0029884   -38.65   0.000     -.121365   -.1096446
      C40MARRIED |   -.051388    .001894   -27.13   0.000    -.0551021   -.0476739
      noncitizen |  -.0709576   .0069802   -10.17   0.000    -.0846457   -.0572696
     C40SCHOOL_E |   -.138775   .0044273   -31.35   0.000    -.1474569    -.130093
     C40SCHOOL_H |  -.0516744   .0045466   -11.37   0.000    -.0605903   -.0427585
     C40SCHOOL_C |          0  (omitted)
     _IC40AGE_12 |   .0399547   .0523749     0.76   0.446     -.062752    .1426613
     _IC40AGE_13 |  -.0227718   .0494341    -0.46   0.645    -.1197116     .074168
     _IC40AGE_14 |  -.0025465   .0495334    -0.05   0.959     -.099681     .094588
     _IC40AGE_15 |  -.0481507   .0492341    -0.98   0.328    -.1446983    .0483969
     _IC40AGE_16 |   .1995021   .0495381     4.03   0.000     .1023585    .2966458
     _IC40AGE_17 |   .1368235    .049067     2.79   0.005     .0406036    .2330433
     _IC40AGE_18 |   .1234128   .0488366     2.53   0.012     .0276448    .2191808
     _IC40AGE_19 |   .0687527    .048758     1.41   0.159    -.0268612    .1643667
     _IC40AGE_20 |   .0681276   .0488124     1.40   0.163    -.0275931    .1638484
     _IC40AGE_21 |   .0487103   .0487768     1.00   0.318    -.0469404    .1443611
     _IC40AGE_22 |   .0344426    .048754     0.71   0.480    -.0611636    .1300488
     _IC40AGE_23 |   .0233527   .0487378     0.48   0.632    -.0722216     .118927
     _IC40AGE_24 |   .0170816   .0487625     0.35   0.726    -.0785413    .1127044
     _IC40AGE_25 |   .0097675   .0488383     0.20   0.842    -.0860039     .105539
     _IC40AGE_26 |  -.0070209     .04881    -0.14   0.886    -.1027367     .088695
     _IC40AGE_27 |  -.0132239   .0487517    -0.27   0.786    -.1088254    .0823777
     _IC40AGE_28 |  -.0162195   .0488273    -0.33   0.740    -.1119692    .0795303
     _IC40AGE_29 |  -.0241168    .048817    -0.49   0.621    -.1198463    .0716127
     _IC40AGE_30 |  -.0213447   .0488005    -0.44   0.662    -.1170421    .0743526
     _IC40AGE_31 |  -.0208955   .0489274    -0.43   0.669    -.1168417    .0750506
     _IC40AGE_32 |  -.0261227   .0488567    -0.53   0.593    -.1219302    .0696848
     _IC40AGE_33 |  -.0372165   .0488225    -0.76   0.446    -.1329569     .058524
     _IC40AGE_34 |  -.0439545   .0488991    -0.90   0.369    -.1398451    .0519362
     _IC40AGE_35 |  -.0500068   .0488579    -1.02   0.306    -.1458166     .045803
     _IC40AGE_36 |  -.0415502   .0489166    -0.85   0.396    -.1374751    .0543748
     _IC40AGE_37 |    -.03121    .048906    -0.64   0.523    -.1271142    .0646941
     _IC40AGE_38 |  -.0328085      .0489    -0.67   0.502    -.1287009    .0630838
     _IC40AGE_39 |  -.0411741   .0489163    -0.84   0.400    -.1370984    .0547502
     _IC40AGE_40 |   -.042141   .0488397    -0.86   0.388    -.1379151    .0536331
           _cons |  -.2763602   .0960796    -2.88   0.004    -.4647713   -.0879491
----------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     countyn |      2315        2315           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est2 stored)

.        qui:    sum  vol if e(sample) == 1

.         estadd local y_mean_round = string(r(mean), "%9.3f")

added macro:
       e(y_mean_round) : "0.147"

.         estadd local sample       = "Army"

added macro:
             e(sample) : "Army"

.         estadd local fe           = "County"

added macro:
                 e(fe) : "County"

. 
. eststo: xi: reghdfe vol  iAAA_PF_farmer iAAA_PF_farmhand                                  farmer farmhand $controls_asn                       
>    if insample == 1 & (cem_matched_farmer == 1 | cem_matched_farmhand == 1), cluster(countyn) absorb(countyn)
i.C40AGE          _IC40AGE_11-40      (naturally coded; _IC40AGE_11 omitted)
(dropped 27 singleton observations)
(MWFE estimator converged in 1 iterations)
note: C40SCHOOL_C omitted because of collinearity

HDFE Linear regression                            Number of obs   =    191,910
Absorbing 1 HDFE group                            F(  41,   2218) =     109.77
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.1683
                                                  Adj R-squared   =     0.1584
                                                  Within R-sq.    =     0.0803
Number of clusters (countyn) =      2,219         Root MSE        =     0.3514

                                (Std. Err. adjusted for 2,219 clusters in countyn)
----------------------------------------------------------------------------------
                 |               Robust
       volunteer |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------+----------------------------------------------------------------
  iAAA_PF_farmer |    18.1484   7.119195     2.55   0.011     4.187414    32.10938
iAAA_PF_farmhand |  -4.125688   5.143067    -0.80   0.423    -14.21142    5.960041
          farmer |  -.1750192   .0418882    -4.18   0.000    -.2571635    -.092875
        farmhand |  -.0089167   .0309666    -0.29   0.773    -.0696432    .0518098
               h |   .3788706   .0766432     4.94   0.000     .2285706    .5291705
               w |  -.0022843   .0009532    -2.40   0.017    -.0041535   -.0004151
             bmi |   .0010477   .0028051     0.37   0.709    -.0044532    .0065486
     C40NONWHITE |   -.138744   .0053679   -25.85   0.000    -.1492706   -.1282174
      C40MARRIED |  -.0589371   .0039284   -15.00   0.000    -.0666409   -.0512334
      noncitizen |  -.0737812   .0194011    -3.80   0.000    -.1118274    -.035735
     C40SCHOOL_E |   -.174006   .0069528   -25.03   0.000    -.1876406   -.1603714
     C40SCHOOL_H |  -.0765016   .0072159   -10.60   0.000    -.0906522    -.062351
     C40SCHOOL_C |          0  (omitted)
     _IC40AGE_12 |  -.0342362   .1416289    -0.24   0.809    -.3119753    .2435029
     _IC40AGE_13 |  -.0988214   .1398264    -0.71   0.480    -.3730258    .1753829
     _IC40AGE_14 |  -.0707475   .1400307    -0.51   0.613    -.3453524    .2038574
     _IC40AGE_15 |   -.130949   .1399234    -0.94   0.349    -.4053435    .1434456
     _IC40AGE_16 |   .1257402   .1402878     0.90   0.370     -.149369    .4008495
     _IC40AGE_17 |   .0893678   .1400702     0.64   0.524    -.1853145    .3640502
     _IC40AGE_18 |   .0697844   .1396746     0.50   0.617    -.2041223     .343691
     _IC40AGE_19 |   .0050648   .1395279     0.04   0.971    -.2685541    .2786837
     _IC40AGE_20 |  -.0047438     .13961    -0.03   0.973    -.2785239    .2690362
     _IC40AGE_21 |  -.0364989   .1394871    -0.26   0.794    -.3100378      .23704
     _IC40AGE_22 |  -.0590393   .1395244    -0.42   0.672    -.3326514    .2145728
     _IC40AGE_23 |  -.0714947    .139466    -0.51   0.608    -.3449922    .2020029
     _IC40AGE_24 |  -.0697321   .1394437    -0.50   0.617    -.3431859    .2037218
     _IC40AGE_25 |  -.0876095    .139597    -0.63   0.530    -.3613639    .1861449
     _IC40AGE_26 |   -.096403   .1394611    -0.69   0.489    -.3698909    .1770848
     _IC40AGE_27 |  -.0905266   .1394811    -0.65   0.516    -.3640539    .1830006
     _IC40AGE_28 |  -.0978285    .139571    -0.70   0.483     -.371532    .1758749
     _IC40AGE_29 |   -.095202   .1395303    -0.68   0.495    -.3688256    .1784217
     _IC40AGE_30 |  -.0897032   .1396939    -0.64   0.521    -.3636477    .1842413
     _IC40AGE_31 |  -.1043095   .1396621    -0.75   0.455    -.3781916    .1695725
     _IC40AGE_32 |  -.1071407   .1395873    -0.77   0.443    -.3808762    .1665949
     _IC40AGE_33 |  -.1185583   .1395169    -0.85   0.396    -.3921558    .1550392
     _IC40AGE_34 |  -.1308683    .139832    -0.94   0.349    -.4050835     .143347
     _IC40AGE_35 |  -.1205037   .1397762    -0.86   0.389    -.3946096    .1536023
     _IC40AGE_36 |  -.1289784   .1398418    -0.92   0.356    -.4032129     .145256
     _IC40AGE_37 |  -.1264864   .1400819    -0.90   0.367    -.4011917     .148219
     _IC40AGE_38 |  -.1045165   .1400309    -0.75   0.456    -.3791218    .1700888
     _IC40AGE_39 |  -.1200091   .1398323    -0.86   0.391     -.394225    .1542068
     _IC40AGE_40 |  -.1223981   .1399705    -0.87   0.382     -.396885    .1520888
           _cons |  -.1412758   .1890934    -0.75   0.455    -.5120944    .2295427
----------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     countyn |      2219        2219           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est3 stored)

.        qui:    sum  vol if e(sample) == 1

.         estadd local y_mean_round = string(r(mean), "%9.3f")

added macro:
       e(y_mean_round) : "0.179"

.         estadd local sample       = "Army: CEM"

added macro:
             e(sample) : "Army: CEM"

.         estadd local fe           = "County"

added macro:
                 e(fe) : "County"

.         
. esttab using  "results/tables/Tab3_main-d.tex"  ,                                                         ///
>        indicate("Age FEs = *AGE*" "Individual controls (military) = $controls_asn_noage" )            ///
>            drop(_cons)                                                                                    ///
>            order(iAAA_PF_farmer iAAA_PF_farmhand farmer farmhand)                                                         ///
>                 mgroups("Volunteer" , pattern(1 0 0)                                                                                          
>                     ///
>                 prefix(\multicolumn{@span}{c}{) suffix(})                                                         ///
>                         span erepeat(\cmidrule(lr){@span}) )                                                                              ///
>                 replace br se  label star(* 0.10 ** 0.05 *** 0.01) obslast nomtitles                                      ///
>                 scalars("fe Fixed effects" "sample Sample:" "y_mean_round Mean dependent variable")           ///
>                 b(%9.3f) se(%9.3f) r2(%9.3f) collabels(none) nonumber                                         ///
>                 nonotes nogaps nolegend title("New Deal and Patriotism: Basic Patterns (Panel D).")
(output written to results/tables/Tab3_main-d.tex)

.                 
. ***************************************************************************************************
. ****         Tab 4. Identification                                                                                 ****
. ***************************************************************************************************
. 
. use "tmp/patriot", clear

. 
. estimates clear

. eststo: xi:  reg iAGRI_PF             iSUM3MO_DROUGHT3340 iAGRI_T73 $control               if sample_ols == 1                      , cluster(C
> LIMDIVX)
i.stateicpsr      _Istateicps_1-98    (naturally coded; _Istateicps_1 omitted)
note: _Istateicps_98 omitted because of collinearity

Linear regression                               Number of obs     =      3,022
                                                F(64, 338)        =          .
                                                Prob > F          =          .
                                                R-squared         =     0.5789
                                                Root MSE          =     .69411

                                    (Std. Err. adjusted for 339 clusters in CLIMDIVX)
-------------------------------------------------------------------------------------
                    |               Robust
           iAGRI_PF |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
iSUM3MO_DROUGHT3340 |   .2862852   .0597948     4.79   0.000     .1686683    .4039021
          iAGRI_T73 |   .2998687   .0796153     3.77   0.000     .1432648    .4564726
         ww1_vol_sh |   .0007242   .0803196     0.01   0.993     -.157265    .1587134
ww1_awards_pop10_is |   .0663441   .1506976     0.44   0.660    -.2300792    .3627673
             lpop30 |  -.1676359   .0422814    -3.96   0.000    -.2508037   -.0844682
           c30unemp |  -1.472645   .6194849    -2.38   0.018    -2.691176   -.2541135
          c30urban1 |    .148546   .0433082     3.43   0.001     .0633586    .2337335
            c30farm |   .3298366   .3020545     1.09   0.276    -.2643068    .9239799
            iYf_T29 |   .2837307   .0720697     3.94   0.000     .1419692    .4254923
           MEAN9628 |   .0086956   .0030049     2.89   0.004     .0027849    .0146062
             c30men |  -1.236684   1.645347    -0.75   0.453    -4.473094    1.999726
           c30black |  -.1929355   .2900599    -0.67   0.506    -.7634854    .3776144
             c30jap |   .2245796   4.425876     0.05   0.960     -8.48115    8.930309
             c30deu |   .6237568   .6041074     1.03   0.303    -.5645269    1.812041
             c30ita |  -1.332877   1.008913    -1.32   0.187    -3.317417    .6516626
             c30vet |   1.575608   .6982832     2.26   0.025     .2020798    2.949136
           lc40wage |   .0803572   .1457565     0.55   0.582    -.2063469    .3670614
      iwarconpro_PC |  -.0118192   .0289969    -0.41   0.684    -.0688563    .0452178
      _Istateicps_2 |   -1.43588   .3440033    -4.17   0.000    -2.112537   -.7592234
      _Istateicps_3 |  -.0402589   .1288011    -0.31   0.755    -.2936116    .2130937
      _Istateicps_4 |  -1.379023   .1627279    -8.47   0.000     -1.69911   -1.058936
      _Istateicps_5 |  -.2991819   .1135336    -2.64   0.009    -.5225034   -.0758604
      _Istateicps_6 |  -1.034047   .1998951    -5.17   0.000    -1.427242   -.6408521
     _Istateicps_11 |  -.4316568   .3317822    -1.30   0.194    -1.084275    .2209612
     _Istateicps_12 |  -.2870182    .179687    -1.60   0.111    -.6404639    .0664275
     _Istateicps_13 |  -1.216242   .1933922    -6.29   0.000    -1.596646   -.8358382
     _Istateicps_14 |  -1.243835    .174084    -7.15   0.000    -1.586259   -.9014102
     _Istateicps_21 |   -.253832   .2816172    -0.90   0.368    -.8077752    .3001111
     _Istateicps_22 |  -.5909109    .264616    -2.23   0.026    -1.111412   -.0704094
     _Istateicps_23 |  -.8642328   .2411458    -3.58   0.000    -1.338568   -.3898972
     _Istateicps_24 |  -.8508278   .2307256    -3.69   0.000    -1.304667   -.3969888
     _Istateicps_25 |  -.5773775   .2544462    -2.27   0.024    -1.077875   -.0768799
     _Istateicps_31 |  -.0240282   .2416335    -0.10   0.921    -.4993231    .4512667
     _Istateicps_32 |   .1105492   .3310292     0.33   0.739    -.5405877     .761686
     _Istateicps_33 |  -.2921672   .3132663    -0.93   0.352    -.9083643    .3240299
     _Istateicps_34 |  -.7874665   .2629334    -2.99   0.003    -1.304658   -.2702746
     _Istateicps_35 |   .0669056   .3246489     0.21   0.837    -.5716813    .7054924
     _Istateicps_36 |   1.146903   .2682436     4.28   0.000     .6192658     1.67454
     _Istateicps_37 |    .473284   .2917803     1.62   0.106    -.1006499    1.047218
     _Istateicps_40 |  -1.137069   .2008682    -5.66   0.000    -1.532178   -.7419597
     _Istateicps_41 |   -.537975   .1995163    -2.70   0.007     -.930425    -.145525
     _Istateicps_42 |   -1.17143   .2348102    -4.99   0.000    -1.633303   -.7095566
     _Istateicps_43 |  -.8949865   .2968767    -3.01   0.003    -1.478945   -.3110278
     _Istateicps_44 |  -.4848957    .212913    -2.28   0.023    -.9036972   -.0660942
     _Istateicps_45 |  -.5737398   .2966003    -1.93   0.054    -1.157155    .0096752
     _Istateicps_46 |  -1.236151   .2605803    -4.74   0.000    -1.748714   -.7235875
     _Istateicps_47 |  -.6703443    .258279    -2.60   0.010    -1.178381   -.1623076
     _Istateicps_48 |  -.7444691   .2630676    -2.83   0.005    -1.261925   -.2270132
     _Istateicps_49 |   -.029522   .3045483    -0.10   0.923    -.6285707    .5695267
     _Istateicps_51 |  -1.113087   .3840741    -2.90   0.004    -1.868563   -.3576103
     _Istateicps_52 |  -.3495761   .2007273    -1.74   0.082    -.7444082    .0452559
     _Istateicps_53 |  -.4779369   .2867284    -1.67   0.096    -1.041934    .0860599
     _Istateicps_54 |  -1.150328   .2268717    -5.07   0.000    -1.596586   -.7040698
     _Istateicps_56 |  -1.614531   .2369028    -6.82   0.000    -2.080521   -1.148542
     _Istateicps_61 |  -.7580026   .4074942    -1.86   0.064    -1.559547    .0435415
     _Istateicps_62 |  -.8764677   .3085737    -2.84   0.005    -1.483434    -.269501
     _Istateicps_63 |  -.4109925   .3109273    -1.32   0.187    -1.022589    .2006037
     _Istateicps_64 |    .145309   .4018568     0.36   0.718    -.6451463    .9357643
     _Istateicps_65 |  -.6095988   .4038237    -1.51   0.132    -1.403923    .1847254
     _Istateicps_66 |  -.3683481    .403032    -0.91   0.361    -1.161115    .4244188
     _Istateicps_67 |  -.5679013   .2816253    -2.02   0.045     -1.12186   -.0139424
     _Istateicps_68 |   .3464281   .3166121     1.09   0.275    -.2763502    .9692064
     _Istateicps_71 |   .2262248   .2408516     0.94   0.348    -.2475321    .6999816
     _Istateicps_72 |  -.5221794   .3207505    -1.63   0.104    -1.153098    .1087391
     _Istateicps_73 |  -.4120003   .3391093    -1.21   0.225    -1.079031    .2550301
     _Istateicps_98 |          0  (omitted)
              _cons |    6.77447   1.585028     4.27   0.000     3.656708    9.892232
-------------------------------------------------------------------------------------
(est1 stored)

.                 qui: sum iAGRI_PF              if e(sample) == 1

. estadd local y_mean_round = string(r(mean), "%9.3f")

added macro:
       e(y_mean_round) : "6.635"

.                 qui: test                    iSUM3MO_DROUGHT3340 iAGRI_T73 

. estadd local F_test       = string(r(F)   , "%9.1f")

added macro:
             e(F_test) : "16.4"

. 
. eststo: xi:  reg iwarbond_1944_PC    iSUM3MO_DROUGHT3340 iAGRI_T73 $control               if sample_ols == 1                      , cluster(CL
> IMDIVX)
i.stateicpsr      _Istateicps_1-98    (naturally coded; _Istateicps_1 omitted)
note: _Istateicps_98 omitted because of collinearity

Linear regression                               Number of obs     =      3,022
                                                F(64, 338)        =          .
                                                Prob > F          =          .
                                                R-squared         =     0.6512
                                                Root MSE          =     .40373

                                    (Std. Err. adjusted for 339 clusters in CLIMDIVX)
-------------------------------------------------------------------------------------
                    |               Robust
   iwarbond_1944_PC |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
iSUM3MO_DROUGHT3340 |   .1044649    .024325     4.29   0.000     .0566174    .1523125
          iAGRI_T73 |   .1080405   .0297961     3.63   0.000     .0494314    .1666495
         ww1_vol_sh |   .0020974   .0364529     0.06   0.954    -.0696057    .0738004
ww1_awards_pop10_is |   .2162091   .0970899     2.23   0.027     .0252326    .4071856
             lpop30 |  -.0420301   .0288695    -1.46   0.146    -.0988165    .0147564
           c30unemp |  -.6593736   .2813952    -2.34   0.020     -1.21288   -.1058673
          c30urban1 |   .0556669   .0264554     2.10   0.036     .0036291    .1077048
            c30farm |   -.531156   .1406302    -3.78   0.000    -.8077767   -.2545353
            iYf_T29 |   .1034498   .0291666     3.55   0.000     .0460789    .1608207
           MEAN9628 |   .0027323   .0011978     2.28   0.023     .0003763    .0050883
             c30men |  -1.473362   .8331646    -1.77   0.078    -3.112203    .1654789
           c30black |  -.2978921   .1084898    -2.75   0.006    -.5112923   -.0844919
             c30jap |   4.449762   2.193753     2.03   0.043     .1346337    8.764891
             c30deu |   .7477781   .2410961     3.10   0.002     .2735402    1.222016
             c30ita |  -.5103324   .6124979    -0.83   0.405     -1.71512    .6944554
             c30vet |   .1354344   1.028509     0.13   0.895     -1.88765    2.158519
           lc40wage |   .4517525   .0618303     7.31   0.000     .3301318    .5733733
      iwarconpro_PC |   .2753167   .0235696    11.68   0.000     .2289551    .3216783
      _Istateicps_2 |  -.2657758   .0859143    -3.09   0.002    -.4347698   -.0967818
      _Istateicps_3 |  -.1851871   .0687087    -2.70   0.007    -.3203375   -.0500366
      _Istateicps_4 |  -.2262059   .0811012    -2.79   0.006    -.3857325   -.0666793
      _Istateicps_5 |  -.3372538   .0447588    -7.53   0.000    -.4252947   -.2492129
      _Istateicps_6 |  -.1067521   .0929128    -1.15   0.251    -.2895123    .0760081
     _Istateicps_11 |   .2263732   .0688665     3.29   0.001     .0909122    .3618342
     _Istateicps_12 |  -.1176232     .09552    -1.23   0.219    -.3055117    .0702652
     _Istateicps_13 |  -.1958528    .063748    -3.07   0.002    -.3212455     -.07046
     _Istateicps_14 |  -.1252031   .0605922    -2.07   0.040    -.2443883   -.0060178
     _Istateicps_21 |  -.0668244   .0954401    -0.70   0.484    -.2545559     .120907
     _Istateicps_22 |  -.1841347   .0936069    -1.97   0.050    -.3682602   -9.23e-06
     _Istateicps_23 |  -.2458621   .0868613    -2.83   0.005     -.416719   -.0750052
     _Istateicps_24 |  -.2665829   .0822878    -3.24   0.001    -.4284435   -.1047223
     _Istateicps_25 |  -.1769377    .105054    -1.68   0.093    -.3835798    .0297043
     _Istateicps_31 |   .3794777   .1139151     3.33   0.001     .1554058    .6035497
     _Istateicps_32 |   .2237409   .1376465     1.63   0.105    -.0470107    .4944926
     _Istateicps_33 |   .1773892   .1347472     1.32   0.189    -.0876596     .442438
     _Istateicps_34 |  -.2124591   .1087525    -1.95   0.052     -.426376    .0014578
     _Istateicps_35 |   .3549817   .1343497     2.64   0.009     .0907147    .6192486
     _Istateicps_36 |   .6300917   .1514888     4.16   0.000     .3321121    .9280713
     _Istateicps_37 |   .2850514   .1180069     2.42   0.016      .052931    .5171719
     _Istateicps_40 |  -.0668447   .0847766    -0.79   0.431    -.2336009    .0999115
     _Istateicps_41 |  -.0528459   .0868975    -0.61   0.544    -.2237739     .118082
     _Istateicps_42 |  -.6301379   .0986893    -6.39   0.000    -.8242606   -.4360152
     _Istateicps_43 |  -.1211772   .1071348    -1.13   0.259    -.3319121    .0895577
     _Istateicps_44 |  -.2319545   .0827767    -2.80   0.005     -.394777   -.0691321
     _Istateicps_45 |  -.3226247   .1057475    -3.05   0.002    -.5306307   -.1146186
     _Istateicps_46 |  -.2446625   .1111285    -2.20   0.028    -.4632531   -.0260719
     _Istateicps_47 |  -.1796429   .0796706    -2.25   0.025    -.3363556   -.0229303
     _Istateicps_48 |  -.5425539   .1011749    -5.36   0.000    -.7415657    -.343542
     _Istateicps_49 |   .0153169   .1116345     0.14   0.891    -.2042691    .2349028
     _Istateicps_51 |  -.5095732   .1827732    -2.79   0.006    -.8690894    -.150057
     _Istateicps_52 |  -.1201319   .0910622    -1.32   0.188    -.2992518     .058988
     _Istateicps_53 |  -.0999809   .1255259    -0.80   0.426    -.3468913    .1469294
     _Istateicps_54 |  -.3753542    .081714    -4.59   0.000    -.5360862   -.2146221
     _Istateicps_56 |  -.3187274   .0791737    -4.03   0.000    -.4744628   -.1629921
     _Istateicps_61 |  -.1338837   .1451198    -0.92   0.357    -.4193354     .151568
     _Istateicps_62 |  -.1844611   .1197032    -1.54   0.124    -.4199182     .050996
     _Istateicps_63 |  -.0207271   .1338542    -0.15   0.877    -.2840193    .2425651
     _Istateicps_64 |   .4946629   .1691118     2.93   0.004     .1620188     .827307
     _Istateicps_65 |  -.0156162   .1628967    -0.10   0.924    -.3360351    .3048028
     _Istateicps_66 |  -.3300368   .1736755    -1.90   0.058    -.6716577    .0115841
     _Istateicps_67 |   -.259308   .1116222    -2.32   0.021    -.4788698   -.0397463
     _Istateicps_68 |    .302222    .137172     2.20   0.028     .0324036    .5720403
     _Istateicps_71 |   .1238927   .1056571     1.17   0.242    -.0839356     .331721
     _Istateicps_72 |   .3660657   .1158076     3.16   0.002     .1382712    .5938601
     _Istateicps_73 |   .3295381   .1579401     2.09   0.038     .0188687    .6402074
     _Istateicps_98 |          0  (omitted)
              _cons |   2.526721   .6197981     4.08   0.000     1.307573    3.745868
-------------------------------------------------------------------------------------
(est2 stored)

.                 qui: sum iwarbond_1944_PC      if e(sample) == 1

. estadd local y_mean_round = string(r(mean), "%9.3f")

added macro:
       e(y_mean_round) : "4.658"

. eststo: xi:  reg ww2_vol_pop40       iSUM3MO_DROUGHT3340 iAGRI_T73 $control               if sample_ols == 1 & servicecommand != 7, cluster(CL
> IMDIVX)
i.stateicpsr      _Istateicps_1-98    (naturally coded; _Istateicps_1 omitted)
note: _Istateicps_31 omitted because of collinearity
note: _Istateicps_32 omitted because of collinearity
note: _Istateicps_33 omitted because of collinearity
note: _Istateicps_34 omitted because of collinearity
note: _Istateicps_35 omitted because of collinearity
note: _Istateicps_36 omitted because of collinearity
note: _Istateicps_37 omitted because of collinearity
note: _Istateicps_62 omitted because of collinearity
note: _Istateicps_68 omitted because of collinearity
note: _Istateicps_98 omitted because of collinearity

Linear regression                               Number of obs     =      2,329
                                                F(55, 265)        =          .
                                                Prob > F          =          .
                                                R-squared         =     0.6326
                                                Root MSE          =     .20971

                                    (Std. Err. adjusted for 266 clusters in CLIMDIVX)
-------------------------------------------------------------------------------------
                    |               Robust
      ww2_vol_pop40 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
iSUM3MO_DROUGHT3340 |   .0329353   .0175951     1.87   0.062    -.0017088    .0675793
          iAGRI_T73 |   .0860219   .0296404     2.90   0.004     .0276613    .1443826
         ww1_vol_sh |   .1130801   .0306323     3.69   0.000     .0527664    .1733938
ww1_awards_pop10_is |   .1064834   .0935613     1.14   0.256    -.0777347    .2907015
             lpop30 |  -.0145244   .0119221    -1.22   0.224    -.0379986    .0089497
           c30unemp |   .5222917   .1937675     2.70   0.007     .1407721    .9038114
          c30urban1 |   .0101617   .0120537     0.84   0.400    -.0135715     .033895
            c30farm |  -.1258121   .0511553    -2.46   0.015    -.2265347   -.0250895
            iYf_T29 |  -.0164674   .0161699    -1.02   0.309    -.0483053    .0153705
           MEAN9628 |  -.0004917   .0008085    -0.61   0.544    -.0020836    .0011001
             c30men |    -1.3743   .5281981    -2.60   0.010    -2.414299   -.3343008
           c30black |  -.4260216   .0587571    -7.25   0.000    -.5417117   -.3103315
             c30jap |  -.0034897    1.72576    -0.00   0.998    -3.401435    3.394456
             c30deu |  -.7035296   .2265722    -3.11   0.002     -1.14964   -.2574188
             c30ita |  -.3215662   .2668771    -1.20   0.229    -.8470355     .203903
             c30vet |   1.085309   .2875075     3.77   0.000     .5192192    1.651399
           lc40wage |   .1889381   .0363711     5.19   0.000      .117325    .2605512
      iwarconpro_PC |  -.0347172    .007519    -4.62   0.000    -.0495218   -.0199127
      _Istateicps_2 |  -.0702053   .0687667    -1.02   0.308    -.2056039    .0651933
      _Istateicps_3 |   .0247341   .0615168     0.40   0.688    -.0963898     .145858
      _Istateicps_4 |   .1492547   .0634771     2.35   0.019     .0242712    .2742383
      _Istateicps_5 |  -.0161633   .0541049    -0.30   0.765    -.1226935     .090367
      _Istateicps_6 |   .2692791   .0669393     4.02   0.000     .1374786    .4010797
     _Istateicps_11 |  -.1809559   .0640584    -2.82   0.005    -.3070841   -.0548276
     _Istateicps_12 |  -.1024822   .0677131    -1.51   0.131    -.2358062    .0308419
     _Istateicps_13 |  -.0277511   .0711003    -0.39   0.697    -.1677446    .1122424
     _Istateicps_14 |  -.2546621   .0626626    -4.06   0.000     -.378042   -.1312822
     _Istateicps_21 |  -.0317785   .0830737    -0.38   0.702    -.1953469      .13179
     _Istateicps_22 |  -.1439841   .0823004    -1.75   0.081    -.3060299    .0180618
     _Istateicps_23 |  -.1099444    .087501    -1.26   0.210      -.28223    .0623412
     _Istateicps_24 |  -.1706729   .0772012    -2.21   0.028    -.3226788    -.018667
     _Istateicps_25 |    .118393   .0899808     1.32   0.189    -.0587753    .2955614
     _Istateicps_31 |          0  (omitted)
     _Istateicps_32 |          0  (omitted)
     _Istateicps_33 |          0  (omitted)
     _Istateicps_34 |          0  (omitted)
     _Istateicps_35 |          0  (omitted)
     _Istateicps_36 |          0  (omitted)
     _Istateicps_37 |          0  (omitted)
     _Istateicps_40 |  -.1688699   .0692587    -2.44   0.015    -.3052372   -.0325026
     _Istateicps_41 |   .0896781   .0774395     1.16   0.248    -.0627969    .2421531
     _Istateicps_42 |  -.3186556   .0825941    -3.86   0.000    -.4812796   -.1560315
     _Istateicps_43 |   .1917461   .0907915     2.11   0.036     .0129817    .3705105
     _Istateicps_44 |   .1642662   .0703968     2.33   0.020      .025658    .3028743
     _Istateicps_45 |  -.1914406   .0740231    -2.59   0.010    -.3371888   -.0456924
     _Istateicps_46 |   .0885733   .0843194     1.05   0.294    -.0774478    .2545945
     _Istateicps_47 |  -.0283112   .0701951    -0.40   0.687    -.1665224       .1099
     _Istateicps_48 |   .0094218   .0931121     0.10   0.919     -.173912    .1927555
     _Istateicps_49 |   .4776769   .0820157     5.82   0.000     .3161917    .6391622
     _Istateicps_51 |  -.0061148   .0816472    -0.07   0.940    -.1668746    .1546449
     _Istateicps_52 |  -.2977252   .0723292    -4.12   0.000    -.4401383   -.1553121
     _Istateicps_53 |   .0896009   .0866352     1.03   0.302    -.0809801    .2601819
     _Istateicps_54 |   -.098141   .1012106    -0.97   0.333    -.2974203    .1011382
     _Istateicps_56 |   .0517802   .0732122     0.71   0.480    -.0923715    .1959319
     _Istateicps_61 |  -.5359364   .0853169    -6.28   0.000    -.7039217   -.3679512
     _Istateicps_62 |          0  (omitted)
     _Istateicps_63 |  -.1087596    .093313    -1.17   0.245    -.2924889    .0749697
     _Istateicps_64 |   .1455702   .0975401     1.49   0.137    -.0464819    .3376224
     _Istateicps_65 |  -.1953069   .1159766    -1.68   0.093    -.4236598     .033046
     _Istateicps_66 |   .0516945   .0889958     0.58   0.562    -.1235343    .2269233
     _Istateicps_67 |  -.2577614   .0844941    -3.05   0.003    -.4241266   -.0913961
     _Istateicps_68 |          0  (omitted)
     _Istateicps_71 |   .0065531   .0889314     0.07   0.941    -.1685489    .1816552
     _Istateicps_72 |  -.2306826    .091039    -2.53   0.012    -.4099345   -.0514308
     _Istateicps_73 |   .0274225   .0864225     0.32   0.751    -.1427396    .1975845
     _Istateicps_98 |          0  (omitted)
              _cons |   .2345152   .3933879     0.60   0.552    -.5400484    1.009079
-------------------------------------------------------------------------------------
(est3 stored)

.                 qui: sum ww2_vol_pop40         if e(sample) == 1

. estadd local y_mean_round = string(r(mean), "%9.3f")

added macro:
       e(y_mean_round) : "0.634"

. eststo: xi:  reg ww2_awards_pop40_is iSUM3MO_DROUGHT3340 iAGRI_T73 $control               if sample_ols == 1 & servicecommand != 7, cluster(CL
> IMDIVX)
i.stateicpsr      _Istateicps_1-98    (naturally coded; _Istateicps_1 omitted)
note: _Istateicps_31 omitted because of collinearity
note: _Istateicps_32 omitted because of collinearity
note: _Istateicps_33 omitted because of collinearity
note: _Istateicps_34 omitted because of collinearity
note: _Istateicps_35 omitted because of collinearity
note: _Istateicps_36 omitted because of collinearity
note: _Istateicps_37 omitted because of collinearity
note: _Istateicps_62 omitted because of collinearity
note: _Istateicps_68 omitted because of collinearity
note: _Istateicps_98 omitted because of collinearity

Linear regression                               Number of obs     =      2,329
                                                F(55, 265)        =          .
                                                Prob > F          =          .
                                                R-squared         =     0.1879
                                                Root MSE          =     .11643

                                    (Std. Err. adjusted for 266 clusters in CLIMDIVX)
-------------------------------------------------------------------------------------
                    |               Robust
ww2_awards_pop40_is |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
iSUM3MO_DROUGHT3340 |   .0130534   .0040664     3.21   0.001     .0050468      .02106
          iAGRI_T73 |   .0145801   .0068482     2.13   0.034     .0010964    .0280639
         ww1_vol_sh |   .0578215   .0203123     2.85   0.005     .0178276    .0978155
ww1_awards_pop10_is |   .0312307   .0376078     0.83   0.407    -.0428173    .1052787
             lpop30 |  -.0188978   .0136521    -1.38   0.167    -.0457781    .0079826
           c30unemp |   .1284953   .1556418     0.83   0.410    -.1779566    .4349473
          c30urban1 |   .0071167   .0062704     1.13   0.257    -.0052295    .0194629
            c30farm |   .0193387   .0252954     0.76   0.445    -.0304667    .0691442
            iYf_T29 |   .0177234   .0099613     1.78   0.076    -.0018899    .0373367
           MEAN9628 |  -.0000508   .0003639    -0.14   0.889    -.0007673    .0006658
             c30men |  -.5675012   .2236623    -2.54   0.012    -1.007882     -.12712
           c30black |  -.0510801   .0216899    -2.36   0.019    -.0937866   -.0083736
             c30jap |   .6928897   1.285392     0.54   0.590    -1.837991     3.22377
             c30deu |   .0579408   .1359466     0.43   0.670    -.2097321    .3256137
             c30ita |  -.0455644   .1905328    -0.24   0.811    -.4207151    .3295864
             c30vet |   .2649923   .1108526     2.39   0.018     .0467283    .4832562
           lc40wage |   .0524457   .0203014     2.58   0.010     .0124732    .0924182
      iwarconpro_PC |   .0046898   .0044781     1.05   0.296    -.0041275     .013507
      _Istateicps_2 |  -.0479245   .0316194    -1.52   0.131    -.1101818    .0143328
      _Istateicps_3 |   -.005522   .0158305    -0.35   0.728    -.0366915    .0256476
      _Istateicps_4 |  -.0506043   .0259912    -1.95   0.053    -.1017799    .0005712
      _Istateicps_5 |   .0540974   .0138931     3.89   0.000     .0267424    .0814524
      _Istateicps_6 |  -.0374051   .0328148    -1.14   0.255     -.102016    .0272059
     _Istateicps_11 |  -.0499485    .023872    -2.09   0.037    -.0969514   -.0029457
     _Istateicps_12 |  -.0414974   .0138913    -2.99   0.003    -.0688487   -.0141461
     _Istateicps_13 |  -.0313463   .0199333    -1.57   0.117    -.0705941    .0079015
     _Istateicps_14 |  -.0525687   .0193714    -2.71   0.007    -.0907101   -.0144273
     _Istateicps_21 |  -.0672694   .0321625    -2.09   0.037    -.1305959   -.0039429
     _Istateicps_22 |  -.0949741   .0308923    -3.07   0.002    -.1557997   -.0341485
     _Istateicps_23 |  -.0692357   .0359144    -1.93   0.055    -.1399497    .0014783
     _Istateicps_24 |   -.054041   .0287452    -1.88   0.061    -.1106391    .0025571
     _Istateicps_25 |  -.1034816   .0466832    -2.22   0.027    -.1953988   -.0115643
     _Istateicps_31 |          0  (omitted)
     _Istateicps_32 |          0  (omitted)
     _Istateicps_33 |          0  (omitted)
     _Istateicps_34 |          0  (omitted)
     _Istateicps_35 |          0  (omitted)
     _Istateicps_36 |          0  (omitted)
     _Istateicps_37 |          0  (omitted)
     _Istateicps_40 |  -.0324607   .0219633    -1.48   0.141    -.0757054    .0107841
     _Istateicps_41 |  -.0312623   .0201221    -1.55   0.121    -.0708818    .0083572
     _Istateicps_42 |  -.0732262    .021761    -3.37   0.001    -.1160727   -.0303797
     _Istateicps_43 |  -.0015287   .0310503    -0.05   0.961    -.0626653    .0596079
     _Istateicps_44 |  -.0422803   .0222767    -1.90   0.059    -.0861421    .0015815
     _Istateicps_45 |  -.0372826   .0197348    -1.89   0.060    -.0761396    .0015744
     _Istateicps_46 |  -.0201272   .0214695    -0.94   0.349    -.0623998    .0221454
     _Istateicps_47 |   -.047039   .0194013    -2.42   0.016    -.0852394   -.0088387
     _Istateicps_48 |  -.0416117    .023251    -1.79   0.075    -.0873918    .0041684
     _Istateicps_49 |  -.0120568   .0221053    -0.55   0.586    -.0555812    .0314676
     _Istateicps_51 |  -.0550907   .0218732    -2.52   0.012    -.0981581   -.0120232
     _Istateicps_52 |  -.0315381   .0301285    -1.05   0.296    -.0908599    .0277837
     _Istateicps_53 |   -.039367   .0235159    -1.67   0.095    -.0856687    .0069347
     _Istateicps_54 |  -.0547425   .0189968    -2.88   0.004    -.0921464   -.0173387
     _Istateicps_56 |  -.0370984   .0194874    -1.90   0.058    -.0754682    .0012715
     _Istateicps_61 |   .0067279   .0466394     0.14   0.885    -.0851031    .0985589
     _Istateicps_62 |          0  (omitted)
     _Istateicps_63 |   -.018745   .0447223    -0.42   0.675    -.1068013    .0693114
     _Istateicps_64 |   .1007132   .0670066     1.50   0.134    -.0312199    .2326464
     _Istateicps_65 |  -.0112761   .0608116    -0.19   0.853    -.1310116    .1084593
     _Istateicps_66 |  -.0235089   .0363542    -0.65   0.518    -.0950887    .0480709
     _Istateicps_67 |  -.0134042   .0401519    -0.33   0.739    -.0924615    .0656531
     _Istateicps_68 |          0  (omitted)
     _Istateicps_71 |   .0618464   .0531292     1.16   0.245    -.0427628    .1664555
     _Istateicps_72 |  -.0404986   .0418042    -0.97   0.334    -.1228093    .0418121
     _Istateicps_73 |   .0128091    .034733     0.37   0.713    -.0555787    .0811969
     _Istateicps_98 |          0  (omitted)
              _cons |   .1792331   .1709717     1.05   0.295    -.1574027    .5158689
-------------------------------------------------------------------------------------
(est4 stored)

.                 qui: sum ww2_awards_pop40_is    if e(sample) == 1

. estadd local y_mean_round = string(r(mean), "%9.3f")

added macro:
       e(y_mean_round) : "0.140"

. eststo: xi:  reg pc1                 iSUM3MO_DROUGHT3340 iAGRI_T73 $control               if sample_ols == 1 & servicecommand != 7, cluster(CL
> IMDIVX)
i.stateicpsr      _Istateicps_1-98    (naturally coded; _Istateicps_1 omitted)
note: _Istateicps_31 omitted because of collinearity
note: _Istateicps_32 omitted because of collinearity
note: _Istateicps_33 omitted because of collinearity
note: _Istateicps_34 omitted because of collinearity
note: _Istateicps_35 omitted because of collinearity
note: _Istateicps_36 omitted because of collinearity
note: _Istateicps_37 omitted because of collinearity
note: _Istateicps_62 omitted because of collinearity
note: _Istateicps_68 omitted because of collinearity
note: _Istateicps_98 omitted because of collinearity

Linear regression                               Number of obs     =      2,329
                                                F(55, 265)        =          .
                                                Prob > F          =          .
                                                R-squared         =     0.6528
                                                Root MSE          =      .7497

                                    (Std. Err. adjusted for 266 clusters in CLIMDIVX)
-------------------------------------------------------------------------------------
                    |               Robust
                pc1 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
iSUM3MO_DROUGHT3340 |   .2109929   .0498625     4.23   0.000     .1128158    .3091699
          iAGRI_T73 |   .2513821   .0855937     2.94   0.004     .0828519    .4199123
         ww1_vol_sh |   .4736309   .1175736     4.03   0.000     .2421336    .7051281
ww1_awards_pop10_is |   .5113822   .2622427     1.95   0.052    -.0049621    1.027727
             lpop30 |  -.1769056    .069036    -2.56   0.011    -.3128345   -.0409767
           c30unemp |   1.189226    .881241     1.35   0.178    -.5458991    2.924351
          c30urban1 |   .1427418     .04682     3.05   0.003     .0505552    .2349283
            c30farm |  -.5731335   .1984474    -2.89   0.004    -.9638679   -.1823992
            iYf_T29 |   .1451992   .0673904     2.15   0.032     .0125106    .2778879
           MEAN9628 |   .0027565   .0022844     1.21   0.229    -.0017414    .0072544
             c30men |  -6.829491   1.469993    -4.65   0.000    -9.723843    -3.93514
           c30black |  -1.193905    .187515    -6.37   0.000    -1.563114   -.8246963
             c30jap |   7.898893   6.744487     1.17   0.243    -5.380707    21.17849
             c30deu |  -.0100055   .8950549    -0.01   0.991    -1.772329    1.752318
             c30ita |  -1.096473   1.215428    -0.90   0.368    -3.489598    1.296653
             c30vet |   3.818315   .8185806     4.66   0.000     2.206565    5.430064
           lc40wage |   .9745861   .1294861     7.53   0.000     .7196335    1.229539
      iwarconpro_PC |   .2301377   .0335567     6.86   0.000     .1640661    .2962093
      _Istateicps_2 |  -.5157156   .1938352    -2.66   0.008    -.8973686   -.1340626
      _Istateicps_3 |  -.1242735   .1585858    -0.78   0.434    -.4365219     .187975
      _Istateicps_4 |  -.1230119   .1732533    -0.71   0.478    -.4641401    .2181162
      _Istateicps_5 |  -.1389388   .1237052    -1.12   0.262    -.3825089    .1046313
      _Istateicps_6 |   .2556518   .2292638     1.12   0.266    -.1957586    .7070621
     _Istateicps_11 |  -.2587251   .1444633    -1.79   0.074    -.5431671    .0257169
     _Istateicps_12 |  -.4482357   .1256271    -3.57   0.000      -.69559   -.2008814
     _Istateicps_13 |  -.3249377   .1716035    -1.89   0.059    -.6628174    .0129421
     _Istateicps_14 |  -.7226172   .1611123    -4.49   0.000     -1.03984    -.405394
     _Istateicps_21 |   -.396342   .2289507    -1.73   0.085    -.8471359    .0544519
     _Istateicps_22 |  -.8164935   .2348209    -3.48   0.001    -1.278845   -.3541415
     _Istateicps_23 |  -.6738436   .2550326    -2.64   0.009    -1.175992   -.1716956
     _Istateicps_24 |  -.7474275   .2170374    -3.44   0.001    -1.174765   -.3200903
     _Istateicps_25 |  -.3973951   .3036161    -1.31   0.192    -.9952019    .2004116
     _Istateicps_31 |          0  (omitted)
     _Istateicps_32 |          0  (omitted)
     _Istateicps_33 |          0  (omitted)
     _Istateicps_34 |          0  (omitted)
     _Istateicps_35 |          0  (omitted)
     _Istateicps_36 |          0  (omitted)
     _Istateicps_37 |          0  (omitted)
     _Istateicps_40 |    -.43819   .1697817    -2.58   0.010    -.7724828   -.1038972
     _Istateicps_41 |   .0198547   .1806826     0.11   0.913    -.3359014    .3756109
     _Istateicps_42 |  -1.371677   .2066606    -6.64   0.000    -1.778583   -.9647718
     _Istateicps_43 |   .2030777   .2574364     0.79   0.431    -.3038033    .7099586
     _Istateicps_44 |  -.0744048   .1858383    -0.40   0.689    -.4403123    .2915027
     _Istateicps_45 |  -.7610023   .1714671    -4.44   0.000    -1.098614    -.423391
     _Istateicps_46 |  -.1379095   .2074969    -0.66   0.507     -.546462    .2706429
     _Istateicps_47 |  -.3639807   .1840314    -1.98   0.049    -.7263305    -.001631
     _Istateicps_48 |   -.632361   .2129032    -2.97   0.003    -1.051558   -.2131639
     _Istateicps_49 |   .7878648     .22647     3.48   0.001     .3419552    1.233774
     _Istateicps_51 |  -.6390116    .202387    -3.16   0.002    -1.037503   -.2405205
     _Istateicps_52 |  -.7073435   .2391226    -2.96   0.003    -1.178165   -.2365215
     _Istateicps_53 |  -.0857699   .2204194    -0.39   0.697    -.5197661    .3482263
     _Istateicps_54 |  -.6600734   .2073406    -3.18   0.002    -1.068318    -.251829
     _Istateicps_56 |  -.3088694   .1835269    -1.68   0.094    -.6702257     .052487
     _Istateicps_61 |  -.9909381   .3426727    -2.89   0.004    -1.665646   -.3162305
     _Istateicps_62 |          0  (omitted)
     _Istateicps_63 |  -.3023885   .3061285    -0.99   0.324    -.9051421    .3003651
     _Istateicps_64 |   1.103207   .3734645     2.95   0.003     .3678721    1.838543
     _Istateicps_65 |  -.4237959   .4255819    -1.00   0.320    -1.261748    .4141563
     _Istateicps_66 |  -.2882373   .3022129    -0.95   0.341    -.8832813    .3068067
     _Istateicps_67 |  -.7303856   .2881037    -2.54   0.012    -1.297649    -.163122
     _Istateicps_68 |          0  (omitted)
     _Istateicps_71 |   .3768838   .2935696     1.28   0.200    -.2011419    .9549094
     _Istateicps_72 |  -.2444381   .2793062    -0.88   0.382    -.7943799    .3055036
     _Istateicps_73 |   .3932247   .2901835     1.36   0.177    -.1781339    .9645832
     _Istateicps_98 |          0  (omitted)
              _cons |  -2.061414   1.174189    -1.76   0.080     -4.37334    .2505121
-------------------------------------------------------------------------------------
(est5 stored)

.                 qui: sum pc1                   if e(sample) == 1

. estadd local y_mean_round = string(r(mean), "%9.3f")

added macro:
       e(y_mean_round) : "-0.012"

. 
. 
. eststo: xi:  ivreg2 iwarbond_1944_PC    (iAGRI_PF = iSUM3MO_DROUGHT3340 iAGRI_T73 ) $control if sample_ols == 1                      , cluster
> (CLIMDIVX) first
i.stateicpsr      _Istateicps_1-98    (naturally coded; _Istateicps_1 omitted)
Warning - collinearities detected
Vars dropped:       _Istateicps_98

First-stage regressions
-----------------------


First-stage regression of iAGRI_PF:

Statistics robust to heteroskedasticity and clustering on CLIMDIVX
Number of obs =                   3022
Number of clusters (CLIMDIVX) =    339
-------------------------------------------------------------------------------------
                    |               Robust
           iAGRI_PF |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
iSUM3MO_DROUGHT3340 |   .2862852   .0597948     4.79   0.000     .1690414    .4035289
          iAGRI_T73 |   .2998687   .0796153     3.77   0.000     .1437617    .4559758
         ww1_vol_sh |   .0007242   .0803196     0.01   0.993    -.1567638    .1582122
ww1_awards_pop10_is |   .0663441   .1506976     0.44   0.660    -.2291388    .3618269
             lpop30 |  -.1676359   .0422814    -3.96   0.000    -.2505399    -.084732
           c30unemp |  -1.472645   .6194849    -2.38   0.018     -2.68731   -.2579794
          c30urban1 |    .148546   .0433082     3.43   0.001     .0636288    .2334632
            c30farm |   .3298366   .3020545     1.09   0.275    -.2624218     .922095
            iYf_T29 |   .2837307   .0720697     3.94   0.000     .1424189    .4250426
           MEAN9628 |   .0086956   .0030049     2.89   0.004     .0028036    .0145875
             c30men |  -1.236684   1.645347    -0.75   0.452    -4.462826    1.989458
           c30black |  -.1929355   .2900599    -0.67   0.506    -.7616753    .3758043
             c30jap |   .2245796   4.425876     0.05   0.960     -8.45353     8.90269
             c30deu |   .6237568   .6041074     1.03   0.302     -.560757    1.808271
             c30ita |  -1.332877   1.008913    -1.32   0.187    -3.311121    .6453665
             c30vet |   1.575608   .6982832     2.26   0.024     .2064374    2.944778
           lc40wage |   .0803572   .1457565     0.55   0.581    -.2054373    .3661518
      iwarconpro_PC |  -.0118192   .0289969    -0.41   0.684    -.0686754    .0450369
      _Istateicps_2 |   -1.43588   .3440033    -4.17   0.000    -2.110391   -.7613702
      _Istateicps_3 |  -.0402589   .1288011    -0.31   0.755    -.2928078    .2122899
      _Istateicps_4 |  -1.379023   .1627279    -8.47   0.000    -1.698094   -1.059951
      _Istateicps_5 |  -.2991819   .1135336    -2.64   0.008    -.5217949   -.0765689
      _Istateicps_6 |  -1.034047   .1998951    -5.17   0.000    -1.425995   -.6420996
     _Istateicps_11 |  -.4316568   .3317822    -1.30   0.193    -1.082204    .2188907
     _Istateicps_12 |  -.2870182    .179687    -1.60   0.110    -.6393426    .0653061
     _Istateicps_13 |  -1.216242   .1933922    -6.29   0.000    -1.595439   -.8370451
     _Istateicps_14 |  -1.243835    .174084    -7.15   0.000    -1.585173   -.9024966
     _Istateicps_21 |   -.253832   .2816172    -0.90   0.367    -.8060178    .2983537
     _Istateicps_22 |  -.5909109    .264616    -2.23   0.026    -1.109761   -.0720608
     _Istateicps_23 |  -.8642328   .2411458    -3.58   0.000    -1.337064   -.3914021
     _Istateicps_24 |  -.8508278   .2307256    -3.69   0.000    -1.303227   -.3984286
     _Istateicps_25 |  -.5773775   .2544462    -2.27   0.023    -1.076287   -.0784677
     _Istateicps_31 |  -.0240282   .2416335    -0.10   0.921    -.4978152    .4497588
     _Istateicps_32 |   .1105492   .3310292     0.33   0.738    -.5385219    .7596202
     _Istateicps_33 |  -.2921672   .3132663    -0.93   0.351    -.9064094    .3220749
     _Istateicps_34 |  -.7874665   .2629334    -2.99   0.003    -1.303018   -.2719154
     _Istateicps_35 |   .0669056   .3246489     0.21   0.837    -.5696553    .7034664
     _Istateicps_36 |   1.146903   .2682436     4.28   0.000     .6209397    1.672866
     _Istateicps_37 |    .473284   .2917803     1.62   0.105    -.0988291    1.045397
     _Istateicps_40 |  -1.137069   .2008682    -5.66   0.000    -1.530925   -.7432132
     _Istateicps_41 |   -.537975   .1995163    -2.70   0.007    -.9291799   -.1467701
     _Istateicps_42 |   -1.17143   .2348102    -4.99   0.000    -1.631838   -.7110219
     _Istateicps_43 |  -.8949865   .2968767    -3.01   0.003    -1.477093   -.3128805
     _Istateicps_44 |  -.4848957    .212913    -2.28   0.023    -.9023686   -.0674229
     _Istateicps_45 |  -.5737398   .2966003    -1.93   0.053    -1.155304    .0078243
     _Istateicps_46 |  -1.236151   .2605803    -4.74   0.000    -1.747088   -.7252136
     _Istateicps_47 |  -.6703443    .258279    -2.60   0.009    -1.176769   -.1639194
     _Istateicps_48 |  -.7444691   .2630676    -2.83   0.005    -1.260283   -.2286549
     _Istateicps_49 |   -.029522   .3045483    -0.10   0.923    -.6266702    .5676262
     _Istateicps_51 |  -1.113087   .3840741    -2.90   0.004    -1.866166   -.3600071
     _Istateicps_52 |  -.3495761   .2007273    -1.74   0.082    -.7431556    .0440033
     _Istateicps_53 |  -.4779369   .2867284    -1.67   0.096    -1.040144    .0842706
     _Istateicps_54 |  -1.150328   .2268717    -5.07   0.000    -1.595171   -.7054856
     _Istateicps_56 |  -1.614531   .2369028    -6.82   0.000    -2.079042    -1.15002
     _Istateicps_61 |  -.7580026   .4074942    -1.86   0.063    -1.557004    .0409985
     _Istateicps_62 |  -.8764677   .3085737    -2.84   0.005    -1.481509   -.2714267
     _Istateicps_63 |  -.4109925   .3109273    -1.32   0.186    -1.020648    .1986634
     _Istateicps_64 |    .145309   .4018568     0.36   0.718    -.6426385    .9332566
     _Istateicps_65 |  -.6095988   .4038237    -1.51   0.131    -1.401403    .1822053
     _Istateicps_66 |  -.3683481    .403032    -0.91   0.361      -1.1586    .4219036
     _Istateicps_67 |  -.5679013   .2816253    -2.02   0.044    -1.120103   -.0156999
     _Istateicps_68 |   .3464281   .3166121     1.09   0.274    -.2743744    .9672306
     _Istateicps_71 |   .2262248   .2408516     0.94   0.348    -.2460291    .6984786
     _Istateicps_72 |  -.5221794   .3207505    -1.63   0.104    -1.151096    .1067375
     _Istateicps_73 |  -.4120003   .3391093    -1.21   0.224    -1.076914    .2529139
     _Istateicps_98 |          0  (omitted)
              _cons |    6.77447   1.585028     4.27   0.000       3.6666    9.882341
-------------------------------------------------------------------------------------
F test of excluded instruments:
  F(  2,   338) =    16.38
  Prob > F      =   0.0000
Sanderson-Windmeijer multivariate F test of excluded instruments:
  F(  2,   338) =    16.38
  Prob > F      =   0.0000



Summary results for first-stage regressions
-------------------------------------------

                                           (Underid)            (Weak id)
Variable     | F(  2,   338)  P-val | SW Chi-sq(  2) P-val | SW F(  2,   338)
iAGRI_PF     |      16.38    0.0000 |       33.59   0.0000 |       16.38

NB: first-stage test statistics cluster-robust

Stock-Yogo weak ID F test critical values for single endogenous regressor:
                                   10% maximal IV size             19.93
                                   15% maximal IV size             11.59
                                   20% maximal IV size              8.75
                                   25% maximal IV size              7.25
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for i.i.d. errors only.

Underidentification test
Ho: matrix of reduced form coefficients has rank=K1-1 (underidentified)
Ha: matrix has rank=K1 (identified)
Kleibergen-Paap rk LM statistic          Chi-sq(2)=16.14    P-val=0.0003

Weak identification test
Ho: equation is weakly identified
Cragg-Donald Wald F statistic                                     134.55
Kleibergen-Paap Wald rk F statistic                                16.38

Stock-Yogo weak ID test critical values for K1=1 and L1=2:
                                   10% maximal IV size             19.93
                                   15% maximal IV size             11.59
                                   20% maximal IV size              8.75
                                   25% maximal IV size              7.25
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.

Weak-instrument-robust inference
Tests of joint significance of endogenous regressors B1 in main equation
Ho: B1=0 and orthogonality conditions are valid
Anderson-Rubin Wald test           F(2,338)=      16.59     P-val=0.0000
Anderson-Rubin Wald test           Chi-sq(2)=     34.01     P-val=0.0000
Stock-Wright LM S statistic        Chi-sq(2)=         .     P-val=     .

NB: Underidentification, weak identification and weak-identification-robust
    test statistics cluster-robust

Number of clusters             N_clust  =        339
Number of observations               N  =       3022
Number of regressors                 K  =         65
Number of endogenous regressors      K1 =          1
Number of instruments                L  =         66
Number of excluded instruments       L1 =          2

IV (2SLS) estimation
--------------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on CLIMDIVX

Number of clusters (CLIMDIVX) =    339                Number of obs =     3022
                                                      F( 64,   338) =   113.12
                                                      Prob > F      =   0.0000
Total (centered) SS     =  1381.251918                Centered R2   =   0.6237
Total (uncentered) SS   =  66940.25714                Uncentered R2 =   0.9922
Residual SS             =  519.6992594                Root MSE      =    .4147

-------------------------------------------------------------------------------------
                    |               Robust
   iwarbond_1944_PC |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
           iAGRI_PF |   .3628581   .0567678     6.39   0.000     .2515951     .474121
         ww1_vol_sh |   .0017971   .0438358     0.04   0.967    -.0841196    .0877138
ww1_awards_pop10_is |   .1921598   .0867236     2.22   0.027     .0221847    .3621349
             lpop30 |   .0188265     .03187     0.59   0.555    -.0436375    .0812905
           c30unemp |  -.1248967   .3260491    -0.38   0.702    -.7639411    .5141477
          c30urban1 |   .0017637   .0295928     0.06   0.952    -.0562371    .0597646
            c30farm |   -.650749   .1625962    -4.00   0.000    -.9694317   -.3320664
            iYf_T29 |   .0004386   .0311344     0.01   0.989    -.0605837     .061461
           MEAN9628 |  -.0004211   .0012784    -0.33   0.742    -.0029266    .0020844
             c30men |  -1.025572    .980402    -1.05   0.296    -2.947125    .8959806
           c30black |  -.2277285   .1186378    -1.92   0.055    -.4602544    .0047973
             c30jap |   4.368221   2.703189     1.62   0.106    -.9299307    9.666374
             c30deu |   .5215383   .2443736     2.13   0.033     .0425749    1.000502
             c30ita |   -.025553   .6606998    -0.04   0.969    -1.320501    1.269395
             c30vet |  -.4359813   1.079444    -0.40   0.686    -2.551652    1.679689
           lc40wage |   .4225714   .0693025     6.10   0.000     .2867411    .5584018
      iwarconpro_PC |   .2796099   .0261571    10.69   0.000     .2283429    .3308768
      _Istateicps_2 |   .2551516   .1994898     1.28   0.201    -.1358411    .6461444
      _Istateicps_3 |  -.1705057   .0932558    -1.83   0.067    -.3532838    .0122724
      _Istateicps_4 |    .273926   .1205731     2.27   0.023      .037607    .5102449
      _Istateicps_5 |  -.2286692   .0692646    -3.30   0.001    -.3644253    -.092913
      _Istateicps_6 |   .2686098   .1470877     1.83   0.068    -.0196768    .5568963
     _Istateicps_11 |   .3830819   .1551284     2.47   0.014     .0790358    .6871279
     _Istateicps_12 |  -.0134074   .0731247    -0.18   0.855    -.1567293    .1299144
     _Istateicps_13 |   .2460354   .0945021     2.60   0.009     .0608147    .4312561
     _Istateicps_14 |   .3265672   .0979723     3.33   0.001      .134545    .5185893
     _Istateicps_21 |   .0267912   .1025767     0.26   0.794    -.1742555    .2278379
     _Istateicps_22 |   .0318381   .0925495     0.34   0.731    -.1495557    .2132318
     _Istateicps_23 |   .0691561   .0924163     0.75   0.454    -.1119765    .2502887
     _Istateicps_24 |   .0434357   .0840696     0.52   0.605    -.1213376    .2082091
     _Istateicps_25 |    .033918   .1015459     0.33   0.738    -.1651083    .2329443
     _Istateicps_31 |   .3896854   .1088369     3.58   0.000      .176369    .6030017
     _Istateicps_32 |   .1851604   .1147327     1.61   0.107    -.0397115    .4100322
     _Istateicps_33 |     .28514   .1104375     2.58   0.010     .0686866    .5015935
     _Istateicps_34 |   .0747433   .0916786     0.82   0.415    -.1049434      .25443
     _Istateicps_35 |   .3328325   .1112062     2.99   0.003     .1148723    .5507927
     _Istateicps_36 |   .2156875   .1828486     1.18   0.238    -.1426892    .5740641
     _Istateicps_37 |   .1152507    .136117     0.85   0.397    -.1515338    .3820351
     _Istateicps_40 |   .3457601   .1260638     2.74   0.006     .0986796    .5928405
     _Istateicps_41 |   .1423102   .1056422     1.35   0.178    -.0647448    .3493652
     _Istateicps_42 |  -.2041263    .115863    -1.76   0.078    -.4312136    .0229609
     _Istateicps_43 |   .2036536     .10849     1.88   0.060    -.0089829    .4162902
     _Istateicps_44 |   -.055948   .1059543    -0.53   0.597    -.2636147    .1517187
     _Istateicps_45 |  -.1142586   .1152874    -0.99   0.322    -.3402178    .1117006
     _Istateicps_46 |   .2041352   .1300239     1.57   0.116    -.0507071    .4589774
     _Istateicps_47 |   .0637409   .1292421     0.49   0.622    -.1895689    .3170507
     _Istateicps_48 |  -.2723034   .1248106    -2.18   0.029    -.5169276   -.0276792
     _Istateicps_49 |    .026546    .116572     0.23   0.820     -.201931     .255023
     _Istateicps_51 |  -.1046667   .1018526    -1.03   0.304    -.3042942    .0949609
     _Istateicps_52 |   .0067989   .1126632     0.06   0.952    -.2140169    .2276147
     _Istateicps_53 |   .0750072   .1031677     0.73   0.467    -.1271978    .2772123
     _Istateicps_54 |   .0425232   .1058323     0.40   0.688    -.1649043    .2499506
     _Istateicps_56 |   .2674249    .139018     1.92   0.054    -.0050453    .5398951
     _Istateicps_61 |   .1422868   .1478795     0.96   0.336    -.1475517    .4321253
     _Istateicps_62 |   .1351795   .0965143     1.40   0.161    -.0539851     .324344
     _Istateicps_63 |   .1302129   .1314135     0.99   0.322    -.1273529    .3877787
     _Istateicps_64 |    .443744   .1256613     3.53   0.000     .1974523    .6900356
     _Istateicps_65 |   .2070832   .1771057     1.17   0.242    -.1400377     .554204
     _Istateicps_66 |  -.1952118   .1419272    -1.38   0.169    -.4733839    .0829604
     _Istateicps_67 |  -.0517882   .0986688    -0.52   0.600    -.2451754     .141599
     _Istateicps_68 |   .1782253   .1527428     1.17   0.243     -.121145    .4775957
     _Istateicps_71 |   .0426895   .1368119     0.31   0.755    -.2254568    .3108358
     _Istateicps_72 |     .55665   .1067046     5.22   0.000     .3475129    .7657871
     _Istateicps_73 |   .4800399   .1269918     3.78   0.000     .2311406    .7289392
     _Istateicps_98 |          0  (omitted)
              _cons |   .0688291   .9278441     0.07   0.941    -1.749712     1.88737
-------------------------------------------------------------------------------------
Underidentification test (Kleibergen-Paap rk LM statistic):             16.143
                                                   Chi-sq(2) P-val =    0.0003
------------------------------------------------------------------------------
Weak identification test (Cragg-Donald Wald F statistic):              134.551
                         (Kleibergen-Paap rk Wald F statistic):         16.384
Stock-Yogo weak ID test critical values: 10% maximal IV size             19.93
                                         15% maximal IV size             11.59
                                         20% maximal IV size              8.75
                                         25% maximal IV size              7.25
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.
------------------------------------------------------------------------------
Warning: estimated covariance matrix of moment conditions not of full rank.
         overidentification statistic not reported, and standard errors and
         model tests should be interpreted with caution.
Possible causes:
         number of clusters insufficient to calculate robust covariance matrix
         singleton dummy variable (dummy with one 1 and N-1 0s or vice versa)
partial option may address problem.
------------------------------------------------------------------------------
Instrumented:         iAGRI_PF
Included instruments: ww1_vol_sh ww1_awards_pop10_is lpop30 c30unemp c30urban1
                      c30farm iYf_T29 MEAN9628 c30men c30black c30jap c30deu
                      c30ita c30vet lc40wage iwarconpro_PC _Istateicps_2
                      _Istateicps_3 _Istateicps_4 _Istateicps_5 _Istateicps_6
                      _Istateicps_11 _Istateicps_12 _Istateicps_13
                      _Istateicps_14 _Istateicps_21 _Istateicps_22
                      _Istateicps_23 _Istateicps_24 _Istateicps_25
                      _Istateicps_31 _Istateicps_32 _Istateicps_33
                      _Istateicps_34 _Istateicps_35 _Istateicps_36
                      _Istateicps_37 _Istateicps_40 _Istateicps_41
                      _Istateicps_42 _Istateicps_43 _Istateicps_44
                      _Istateicps_45 _Istateicps_46 _Istateicps_47
                      _Istateicps_48 _Istateicps_49 _Istateicps_51
                      _Istateicps_52 _Istateicps_53 _Istateicps_54
                      _Istateicps_56 _Istateicps_61 _Istateicps_62
                      _Istateicps_63 _Istateicps_64 _Istateicps_65
                      _Istateicps_66 _Istateicps_67 _Istateicps_68
                      _Istateicps_71 _Istateicps_72 _Istateicps_73
Excluded instruments: iSUM3MO_DROUGHT3340 iAGRI_T73
Dropped collinear:    _Istateicps_98
------------------------------------------------------------------------------
(est6 stored)

. estadd local RA_test = string(`e(arfp)', "%4.3f")

added macro:
            e(RA_test) : "0.000"

.                 qui:   sum  iwarbond_1944_PC   if e(sample) == 1, d

. estadd local y_mean_round = string(r(mean), "%9.3f")

added macro:
       e(y_mean_round) : "4.658"

.        local iqr_y       = (r(p75) - r(p25))

. estadd local IQR_Y = string(`iqr_y', "%9.3f")

added macro:
              e(IQR_Y) : "0.921"

.             qui: sum iAGRI_PF              if e(sample) == 1, d

.        local iqr_x       = (r(p75) - r(p25))*_b[iAGRI_PF]

. estadd local IQR_X = string(`iqr_x', "%9.3f")

added macro:
              e(IQR_X) : "0.493"

.        local iqr_xdY       = (`iqr_x' / `iqr_y')*100

. estadd local IQR_XY = string(`iqr_xdY', "%9.1f") + "\%"

added macro:
             e(IQR_XY) : "53.5\%"

. 
. 
. eststo: xi:  ivreg2 ww2_vol_pop40       (iAGRI_PF = iSUM3MO_DROUGHT3340 iAGRI_T73 ) $control if sample_ols == 1 & servicecommand != 7, cluster
> (CLIMDIVX) first
i.stateicpsr      _Istateicps_1-98    (naturally coded; _Istateicps_1 omitted)
Warning - collinearities detected
Vars dropped:       _Istateicps_31 _Istateicps_32 _Istateicps_33 _Istateicps_34
                    _Istateicps_35 _Istateicps_36 _Istateicps_37 _Istateicps_62
                    _Istateicps_68 _Istateicps_98

First-stage regressions
-----------------------


First-stage regression of iAGRI_PF:

Statistics robust to heteroskedasticity and clustering on CLIMDIVX
Number of obs =                   2329
Number of clusters (CLIMDIVX) =    266
-------------------------------------------------------------------------------------
                    |               Robust
           iAGRI_PF |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
iSUM3MO_DROUGHT3340 |   .3017194   .0620357     4.86   0.000     .1800669     .423372
          iAGRI_T73 |   .2151504   .1027182     2.09   0.036     .0137191    .4165817
         ww1_vol_sh |   .0541683   .0996935     0.54   0.587    -.1413316    .2496681
ww1_awards_pop10_is |      .0621    .178696     0.35   0.728    -.2883244    .4125244
             lpop30 |  -.1977218    .045403    -4.35   0.000    -.2867574   -.1086861
           c30unemp |   -1.11257   .6676518    -1.67   0.096    -2.421841     .196701
          c30urban1 |   .1635703   .0463311     3.53   0.000     .0727146    .2544259
            c30farm |   .0915259   .3156527     0.29   0.772    -.5274718    .7105237
            iYf_T29 |    .341843   .0844944     4.05   0.000     .1761488    .5075372
           MEAN9628 |   .0106535   .0032477     3.28   0.001     .0042847    .0170223
             c30men |  -.3652069    1.86481    -0.20   0.845    -4.022115    3.291701
           c30black |   -.264047   .2875082    -0.92   0.359    -.8278531    .2997591
             c30jap |  -4.334511   5.246493    -0.83   0.409    -14.62293    5.953907
             c30deu |   .6765578   1.035268     0.65   0.513    -1.353611    2.706727
             c30ita |   -1.61388   1.094103    -1.48   0.140    -3.759426    .5316646
             c30vet |   .7112819   .6953677     1.02   0.306    -.6523402    2.074904
           lc40wage |   .0876162   .1586872     0.55   0.581    -.2235707    .3988032
      iwarconpro_PC |   .0034168     .03335     0.10   0.918    -.0619829    .0688165
      _Istateicps_2 |  -1.412081   .3550796    -3.98   0.000    -2.108395   -.7157667
      _Istateicps_3 |  -.0378801   .1325542    -0.29   0.775    -.2978201    .2220599
      _Istateicps_4 |  -1.347562   .1733416    -7.77   0.000    -1.687486   -1.007638
      _Istateicps_5 |  -.3293426   .1130741    -2.91   0.004     -.551082   -.1076033
      _Istateicps_6 |  -.9843088   .2043601    -4.82   0.000    -1.385061   -.5835568
     _Istateicps_11 |  -.4291463   .3273146    -1.31   0.190    -1.071013    .2127205
     _Istateicps_12 |  -.3323729   .1866564    -1.78   0.075    -.6984076    .0336618
     _Istateicps_13 |  -1.199832   .1961727    -6.12   0.000    -1.584529   -.8151361
     _Istateicps_14 |  -1.239489   .1771007    -7.00   0.000    -1.586785   -.8921928
     _Istateicps_21 |  -.2387278   .2920916    -0.82   0.414    -.8115219    .3340663
     _Istateicps_22 |  -.5942314   .2704594    -2.20   0.028    -1.124605   -.0638582
     _Istateicps_23 |   -.849258   .2552081    -3.33   0.001    -1.349723   -.3487926
     _Istateicps_24 |  -.8600766   .2368249    -3.63   0.000    -1.324492   -.3956609
     _Istateicps_25 |  -.5458066   .2935731    -1.86   0.063    -1.121506    .0298927
     _Istateicps_31 |          0  (omitted)
     _Istateicps_32 |          0  (omitted)
     _Istateicps_33 |          0  (omitted)
     _Istateicps_34 |          0  (omitted)
     _Istateicps_35 |          0  (omitted)
     _Istateicps_36 |          0  (omitted)
     _Istateicps_37 |          0  (omitted)
     _Istateicps_40 |  -1.060045    .205751    -5.15   0.000    -1.463524   -.6565654
     _Istateicps_41 |  -.4192332   .2074482    -2.02   0.043     -.826041   -.0124254
     _Istateicps_42 |  -1.069833   .2409245    -4.44   0.000    -1.542288   -.5973781
     _Istateicps_43 |  -.9161689   .2840917    -3.22   0.001    -1.473275   -.3590627
     _Istateicps_44 |  -.3887811   .2208118    -1.76   0.078    -.8217948    .0442327
     _Istateicps_45 |  -.5342521   .3042204    -1.76   0.079    -1.130831    .0623268
     _Istateicps_46 |  -1.144274   .2653921    -4.31   0.000     -1.66471   -.6238378
     _Istateicps_47 |  -.5713226   .2581934    -2.21   0.027    -1.077642   -.0650031
     _Istateicps_48 |   -.646538   .2591545    -2.49   0.013    -1.154742   -.1383339
     _Istateicps_49 |   .0685505   .3198109     0.21   0.830    -.5586015    .6957024
     _Istateicps_51 |  -1.033064   .3703717    -2.79   0.005    -1.759366   -.3067616
     _Istateicps_52 |  -.3209361   .2026502    -1.58   0.113     -.718335    .0764628
     _Istateicps_53 |  -.3890901   .2988818    -1.30   0.193    -.9751999    .1970198
     _Istateicps_54 |  -1.027017    .232123    -4.42   0.000    -1.482213   -.5718221
     _Istateicps_56 |  -1.548947   .2443366    -6.34   0.000    -2.028093   -1.069801
     _Istateicps_61 |  -.7121697   .4108419    -1.73   0.083    -1.517834    .0934948
     _Istateicps_62 |          0  (omitted)
     _Istateicps_63 |  -.4025677   .3355926    -1.20   0.230    -1.060668    .2555323
     _Istateicps_64 |   .2287702   .4423076     0.52   0.605    -.6385989    1.096139
     _Istateicps_65 |  -.6859005   .4379341    -1.57   0.117    -1.544693     .172892
     _Istateicps_66 |  -.2591229   .4164294    -0.62   0.534    -1.075745    .5574987
     _Istateicps_67 |  -.5636995   .3013475    -1.87   0.062    -1.154645    .0272456
     _Istateicps_68 |          0  (omitted)
     _Istateicps_71 |   .3021226   .2625017     1.15   0.250    -.2126456    .8168907
     _Istateicps_72 |  -.4572427   .3564004    -1.28   0.200    -1.156147    .2416616
     _Istateicps_73 |  -.3817661   .3529455    -1.08   0.280    -1.073895     .310363
     _Istateicps_98 |          0  (omitted)
              _cons |   6.394125   1.802429     3.55   0.000     2.859547    9.928704
-------------------------------------------------------------------------------------
F test of excluded instruments:
  F(  2,   265) =    12.62
  Prob > F      =   0.0000
Sanderson-Windmeijer multivariate F test of excluded instruments:
  F(  2,   265) =    12.62
  Prob > F      =   0.0000



Summary results for first-stage regressions
-------------------------------------------

                                           (Underid)            (Weak id)
Variable     | F(  2,   265)  P-val | SW Chi-sq(  2) P-val | SW F(  2,   265)
iAGRI_PF     |      12.62    0.0000 |       25.97   0.0000 |       12.62

NB: first-stage test statistics cluster-robust

Stock-Yogo weak ID F test critical values for single endogenous regressor:
                                   10% maximal IV size             19.93
                                   15% maximal IV size             11.59
                                   20% maximal IV size              8.75
                                   25% maximal IV size              7.25
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for i.i.d. errors only.

Underidentification test
Ho: matrix of reduced form coefficients has rank=K1-1 (underidentified)
Ha: matrix has rank=K1 (identified)
Kleibergen-Paap rk LM statistic          Chi-sq(2)=18.45    P-val=0.0001

Weak identification test
Ho: equation is weakly identified
Cragg-Donald Wald F statistic                                      93.33
Kleibergen-Paap Wald rk F statistic                                12.62

Stock-Yogo weak ID test critical values for K1=1 and L1=2:
                                   10% maximal IV size             19.93
                                   15% maximal IV size             11.59
                                   20% maximal IV size              8.75
                                   25% maximal IV size              7.25
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.

Weak-instrument-robust inference
Tests of joint significance of endogenous regressors B1 in main equation
Ho: B1=0 and orthogonality conditions are valid
Anderson-Rubin Wald test           F(2,265)=       4.58     P-val=0.0111
Anderson-Rubin Wald test           Chi-sq(2)=      9.41     P-val=0.0090
Stock-Wright LM S statistic        Chi-sq(2)=         .     P-val=     .

NB: Underidentification, weak identification and weak-identification-robust
    test statistics cluster-robust

Number of clusters             N_clust  =        266
Number of observations               N  =       2329
Number of regressors                 K  =         56
Number of endogenous regressors      K1 =          1
Number of instruments                L  =         57
Number of excluded instruments       L1 =          2

IV (2SLS) estimation
--------------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on CLIMDIVX

Number of clusters (CLIMDIVX) =    266                Number of obs =     2329
                                                      F( 55,   265) =   251.33
                                                      Prob > F      =   0.0000
Total (centered) SS     =  271.9374693                Centered R2   =   0.5199
Total (uncentered) SS   =  1207.797255                Uncentered R2 =   0.8919
Residual SS             =  130.5650451                Root MSE      =    .2368

-------------------------------------------------------------------------------------
                    |               Robust
      ww2_vol_pop40 |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
           iAGRI_PF |   .1868916   .0533392     3.50   0.000     .0823487    .2914344
         ww1_vol_sh |   .1055582    .035724     2.95   0.003     .0355405    .1755759
ww1_awards_pop10_is |   .0997412   .0921658     1.08   0.279    -.0809005    .2803829
             lpop30 |    .020982   .0198356     1.06   0.290     -.017895    .0598591
           c30unemp |   .7409981   .2857237     2.59   0.010       .18099    1.301006
          c30urban1 |  -.0207848   .0170628    -1.22   0.223    -.0542274    .0126578
            c30farm |  -.1391921   .0791611    -1.76   0.079     -.294345    .0159609
            iYf_T29 |  -.0773547   .0269029    -2.88   0.004    -.1300833   -.0246261
           MEAN9628 |  -.0024648   .0010444    -2.36   0.018    -.0045118   -.0004178
             c30men |  -1.263337   .6120958    -2.06   0.039    -2.463023   -.0636518
           c30black |  -.3873637   .0665045    -5.82   0.000    -.5177102   -.2570173
             c30jap |   .8512667   1.551103     0.55   0.583    -2.188838    3.891372
             c30deu |  -.8447066   .1877555    -4.50   0.000    -1.212701   -.4767124
             c30ita |  -.0688082   .3025835    -0.23   0.820     -.661861    .5242447
             c30vet |    .945918   .2852897     3.32   0.001     .3867605    1.505076
           lc40wage |   .1775205   .0452079     3.93   0.000     .0889146    .2661264
      iwarconpro_PC |  -.0352934    .010795    -3.27   0.001    -.0564511   -.0141357
      _Istateicps_2 |   .2008432   .1075048     1.87   0.062    -.0098623    .4115488
      _Istateicps_3 |   .0285577   .0792425     0.36   0.719    -.1267548    .1838702
      _Istateicps_4 |   .4183864   .1007922     4.15   0.000     .2208373    .6159354
      _Istateicps_5 |    .043889    .071236     0.62   0.538    -.0957311    .1835091
      _Istateicps_6 |   .4468934   .0984851     4.54   0.000     .2538663    .6399206
     _Istateicps_11 |  -.1043796   .1073376    -0.97   0.331    -.3147575    .1059983
     _Istateicps_12 |  -.0433512   .0973179    -0.45   0.656    -.2340908    .1473883
     _Istateicps_13 |   .1761743   .0954781     1.85   0.065    -.0109593    .3633079
     _Istateicps_14 |  -.0399175    .092943    -0.43   0.668    -.2220825    .1422475
     _Istateicps_21 |  -.0481837   .0837007    -0.58   0.565    -.2122341    .1158666
     _Istateicps_22 |  -.0969536   .0864092    -1.12   0.262    -.2663126    .0724054
     _Istateicps_23 |  -.0076968   .0958399    -0.08   0.936    -.1955396     .180146
     _Istateicps_24 |  -.0610299   .0811486    -0.75   0.452    -.2200782    .0980185
     _Istateicps_25 |   .1698956   .0951242     1.79   0.074    -.0165443    .3563355
     _Istateicps_31 |          0  (omitted)
     _Istateicps_32 |          0  (omitted)
     _Istateicps_33 |          0  (omitted)
     _Istateicps_34 |          0  (omitted)
     _Istateicps_35 |          0  (omitted)
     _Istateicps_36 |          0  (omitted)
     _Istateicps_37 |          0  (omitted)
     _Istateicps_40 |   .0268403   .0997686     0.27   0.788    -.1687025    .2223831
     _Istateicps_41 |    .168629   .0941446     1.79   0.073     -.015891     .353149
     _Istateicps_42 |  -.1542304   .0842857    -1.83   0.067    -.3194274    .0109666
     _Istateicps_43 |    .359333   .1030183     3.49   0.000     .1574208    .5612453
     _Istateicps_44 |   .2335672   .0866726     2.69   0.007     .0636921    .4034423
     _Istateicps_45 |   -.101439   .0990457    -1.02   0.306     -.295565     .092687
     _Istateicps_46 |   .2923887   .0978264     2.99   0.003     .1006525     .484125
     _Istateicps_47 |   .0710973   .0975737     0.73   0.466    -.1201436    .2623383
     _Istateicps_48 |   .1294789   .0963612     1.34   0.179    -.0593855    .3183432
     _Istateicps_49 |   .4488245   .0959304     4.68   0.000     .2608044    .6368446
     _Istateicps_51 |   .1447727   .1261021     1.15   0.251    -.1023828    .3919282
     _Istateicps_52 |  -.2417397   .0886653    -2.73   0.006    -.4155205    -.067959
     _Istateicps_53 |   .0980757   .1016146     0.97   0.334    -.1010852    .2972366
     _Istateicps_54 |   .0772363   .1058926     0.73   0.466    -.1303093     .284782
     _Istateicps_56 |   .3277989    .117535     2.79   0.005     .0974344    .5581633
     _Istateicps_61 |  -.4500034   .1014462    -4.44   0.000    -.6488343   -.2511725
     _Istateicps_62 |          0  (omitted)
     _Istateicps_63 |  -.1089466   .0967547    -1.13   0.260    -.2985822    .0806891
     _Istateicps_64 |   .0280387   .1166365     0.24   0.810    -.2005646    .2566419
     _Istateicps_65 |  -.1306264   .1092645    -1.20   0.232    -.3447808     .083528
     _Istateicps_66 |   .0528292   .0961077     0.55   0.583    -.1355384    .2411969
     _Istateicps_67 |  -.2125683   .0876886    -2.42   0.015    -.3844348   -.0407017
     _Istateicps_68 |          0  (omitted)
     _Istateicps_71 |  -.0863682   .1053114    -0.82   0.412    -.2927747    .1200382
     _Istateicps_72 |   -.185053   .0977885    -1.89   0.058     -.376715     .006609
     _Istateicps_73 |   .0570815   .0941405     0.61   0.544    -.1274306    .2415935
     _Istateicps_98 |          0  (omitted)
              _cons |  -1.007403   .7102966    -1.42   0.156    -2.399559    .3847522
-------------------------------------------------------------------------------------
Underidentification test (Kleibergen-Paap rk LM statistic):             18.451
                                                   Chi-sq(2) P-val =    0.0001
------------------------------------------------------------------------------
Weak identification test (Cragg-Donald Wald F statistic):               93.332
                         (Kleibergen-Paap rk Wald F statistic):         12.625
Stock-Yogo weak ID test critical values: 10% maximal IV size             19.93
                                         15% maximal IV size             11.59
                                         20% maximal IV size              8.75
                                         25% maximal IV size              7.25
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.
------------------------------------------------------------------------------
Warning: estimated covariance matrix of moment conditions not of full rank.
         overidentification statistic not reported, and standard errors and
         model tests should be interpreted with caution.
Possible causes:
         number of clusters insufficient to calculate robust covariance matrix
         singleton dummy variable (dummy with one 1 and N-1 0s or vice versa)
partial option may address problem.
------------------------------------------------------------------------------
Instrumented:         iAGRI_PF
Included instruments: ww1_vol_sh ww1_awards_pop10_is lpop30 c30unemp c30urban1
                      c30farm iYf_T29 MEAN9628 c30men c30black c30jap c30deu
                      c30ita c30vet lc40wage iwarconpro_PC _Istateicps_2
                      _Istateicps_3 _Istateicps_4 _Istateicps_5 _Istateicps_6
                      _Istateicps_11 _Istateicps_12 _Istateicps_13
                      _Istateicps_14 _Istateicps_21 _Istateicps_22
                      _Istateicps_23 _Istateicps_24 _Istateicps_25
                      _Istateicps_40 _Istateicps_41 _Istateicps_42
                      _Istateicps_43 _Istateicps_44 _Istateicps_45
                      _Istateicps_46 _Istateicps_47 _Istateicps_48
                      _Istateicps_49 _Istateicps_51 _Istateicps_52
                      _Istateicps_53 _Istateicps_54 _Istateicps_56
                      _Istateicps_61 _Istateicps_63 _Istateicps_64
                      _Istateicps_65 _Istateicps_66 _Istateicps_67
                      _Istateicps_71 _Istateicps_72 _Istateicps_73
Excluded instruments: iSUM3MO_DROUGHT3340 iAGRI_T73
Dropped collinear:    _Istateicps_31 _Istateicps_32 _Istateicps_33
                      _Istateicps_34 _Istateicps_35 _Istateicps_36
                      _Istateicps_37 _Istateicps_62 _Istateicps_68
                      _Istateicps_98
------------------------------------------------------------------------------
(est7 stored)

. estadd local RA_test = string(`e(arfp)', "%4.3f")

added macro:
            e(RA_test) : "0.011"

.                 qui:   sum  ww2_vol_pop40      if e(sample) == 1, d

. estadd local y_mean_round = string(r(mean), "%9.3f")

added macro:
       e(y_mean_round) : "0.634"

.        local iqr_y       = (r(p75) - r(p25))

. estadd local IQR_Y = string(`iqr_y', "%9.3f")

added macro:
              e(IQR_Y) : "0.402"

.             qui: sum iAGRI_PF              if e(sample) == 1, d

.        local iqr_x       = (r(p75) - r(p25))*_b[iAGRI_PF]

. estadd local IQR_X = string(`iqr_x', "%9.3f")

added macro:
              e(IQR_X) : "0.207"

.        local iqr_xdY       = (`iqr_x' / `iqr_y')*100

. estadd local IQR_XY = string(`iqr_xdY', "%9.1f") + "\%"

added macro:
             e(IQR_XY) : "51.6\%"

. 
. eststo: xi:  ivreg2 ww2_awards_pop40_is (iAGRI_PF = iSUM3MO_DROUGHT3340 iAGRI_T73 ) $control if sample_ols == 1 & servicecommand != 7, cluster
> (CLIMDIVX) first
i.stateicpsr      _Istateicps_1-98    (naturally coded; _Istateicps_1 omitted)
Warning - collinearities detected
Vars dropped:       _Istateicps_31 _Istateicps_32 _Istateicps_33 _Istateicps_34
                    _Istateicps_35 _Istateicps_36 _Istateicps_37 _Istateicps_62
                    _Istateicps_68 _Istateicps_98

First-stage regressions
-----------------------


First-stage regression of iAGRI_PF:

Statistics robust to heteroskedasticity and clustering on CLIMDIVX
Number of obs =                   2329
Number of clusters (CLIMDIVX) =    266
-------------------------------------------------------------------------------------
                    |               Robust
           iAGRI_PF |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
iSUM3MO_DROUGHT3340 |   .3017194   .0620357     4.86   0.000     .1800669     .423372
          iAGRI_T73 |   .2151504   .1027182     2.09   0.036     .0137191    .4165817
         ww1_vol_sh |   .0541683   .0996935     0.54   0.587    -.1413316    .2496681
ww1_awards_pop10_is |      .0621    .178696     0.35   0.728    -.2883244    .4125244
             lpop30 |  -.1977218    .045403    -4.35   0.000    -.2867574   -.1086861
           c30unemp |   -1.11257   .6676518    -1.67   0.096    -2.421841     .196701
          c30urban1 |   .1635703   .0463311     3.53   0.000     .0727146    .2544259
            c30farm |   .0915259   .3156527     0.29   0.772    -.5274718    .7105237
            iYf_T29 |    .341843   .0844944     4.05   0.000     .1761488    .5075372
           MEAN9628 |   .0106535   .0032477     3.28   0.001     .0042847    .0170223
             c30men |  -.3652069    1.86481    -0.20   0.845    -4.022115    3.291701
           c30black |   -.264047   .2875082    -0.92   0.359    -.8278531    .2997591
             c30jap |  -4.334511   5.246493    -0.83   0.409    -14.62293    5.953907
             c30deu |   .6765578   1.035268     0.65   0.513    -1.353611    2.706727
             c30ita |   -1.61388   1.094103    -1.48   0.140    -3.759426    .5316646
             c30vet |   .7112819   .6953677     1.02   0.306    -.6523402    2.074904
           lc40wage |   .0876162   .1586872     0.55   0.581    -.2235707    .3988032
      iwarconpro_PC |   .0034168     .03335     0.10   0.918    -.0619829    .0688165
      _Istateicps_2 |  -1.412081   .3550796    -3.98   0.000    -2.108395   -.7157667
      _Istateicps_3 |  -.0378801   .1325542    -0.29   0.775    -.2978201    .2220599
      _Istateicps_4 |  -1.347562   .1733416    -7.77   0.000    -1.687486   -1.007638
      _Istateicps_5 |  -.3293426   .1130741    -2.91   0.004     -.551082   -.1076033
      _Istateicps_6 |  -.9843088   .2043601    -4.82   0.000    -1.385061   -.5835568
     _Istateicps_11 |  -.4291463   .3273146    -1.31   0.190    -1.071013    .2127205
     _Istateicps_12 |  -.3323729   .1866564    -1.78   0.075    -.6984076    .0336618
     _Istateicps_13 |  -1.199832   .1961727    -6.12   0.000    -1.584529   -.8151361
     _Istateicps_14 |  -1.239489   .1771007    -7.00   0.000    -1.586785   -.8921928
     _Istateicps_21 |  -.2387278   .2920916    -0.82   0.414    -.8115219    .3340663
     _Istateicps_22 |  -.5942314   .2704594    -2.20   0.028    -1.124605   -.0638582
     _Istateicps_23 |   -.849258   .2552081    -3.33   0.001    -1.349723   -.3487926
     _Istateicps_24 |  -.8600766   .2368249    -3.63   0.000    -1.324492   -.3956609
     _Istateicps_25 |  -.5458066   .2935731    -1.86   0.063    -1.121506    .0298927
     _Istateicps_31 |          0  (omitted)
     _Istateicps_32 |          0  (omitted)
     _Istateicps_33 |          0  (omitted)
     _Istateicps_34 |          0  (omitted)
     _Istateicps_35 |          0  (omitted)
     _Istateicps_36 |          0  (omitted)
     _Istateicps_37 |          0  (omitted)
     _Istateicps_40 |  -1.060045    .205751    -5.15   0.000    -1.463524   -.6565654
     _Istateicps_41 |  -.4192332   .2074482    -2.02   0.043     -.826041   -.0124254
     _Istateicps_42 |  -1.069833   .2409245    -4.44   0.000    -1.542288   -.5973781
     _Istateicps_43 |  -.9161689   .2840917    -3.22   0.001    -1.473275   -.3590627
     _Istateicps_44 |  -.3887811   .2208118    -1.76   0.078    -.8217948    .0442327
     _Istateicps_45 |  -.5342521   .3042204    -1.76   0.079    -1.130831    .0623268
     _Istateicps_46 |  -1.144274   .2653921    -4.31   0.000     -1.66471   -.6238378
     _Istateicps_47 |  -.5713226   .2581934    -2.21   0.027    -1.077642   -.0650031
     _Istateicps_48 |   -.646538   .2591545    -2.49   0.013    -1.154742   -.1383339
     _Istateicps_49 |   .0685505   .3198109     0.21   0.830    -.5586015    .6957024
     _Istateicps_51 |  -1.033064   .3703717    -2.79   0.005    -1.759366   -.3067616
     _Istateicps_52 |  -.3209361   .2026502    -1.58   0.113     -.718335    .0764628
     _Istateicps_53 |  -.3890901   .2988818    -1.30   0.193    -.9751999    .1970198
     _Istateicps_54 |  -1.027017    .232123    -4.42   0.000    -1.482213   -.5718221
     _Istateicps_56 |  -1.548947   .2443366    -6.34   0.000    -2.028093   -1.069801
     _Istateicps_61 |  -.7121697   .4108419    -1.73   0.083    -1.517834    .0934948
     _Istateicps_62 |          0  (omitted)
     _Istateicps_63 |  -.4025677   .3355926    -1.20   0.230    -1.060668    .2555323
     _Istateicps_64 |   .2287702   .4423076     0.52   0.605    -.6385989    1.096139
     _Istateicps_65 |  -.6859005   .4379341    -1.57   0.117    -1.544693     .172892
     _Istateicps_66 |  -.2591229   .4164294    -0.62   0.534    -1.075745    .5574987
     _Istateicps_67 |  -.5636995   .3013475    -1.87   0.062    -1.154645    .0272456
     _Istateicps_68 |          0  (omitted)
     _Istateicps_71 |   .3021226   .2625017     1.15   0.250    -.2126456    .8168907
     _Istateicps_72 |  -.4572427   .3564004    -1.28   0.200    -1.156147    .2416616
     _Istateicps_73 |  -.3817661   .3529455    -1.08   0.280    -1.073895     .310363
     _Istateicps_98 |          0  (omitted)
              _cons |   6.394125   1.802429     3.55   0.000     2.859547    9.928704
-------------------------------------------------------------------------------------
F test of excluded instruments:
  F(  2,   265) =    12.62
  Prob > F      =   0.0000
Sanderson-Windmeijer multivariate F test of excluded instruments:
  F(  2,   265) =    12.62
  Prob > F      =   0.0000



Summary results for first-stage regressions
-------------------------------------------

                                           (Underid)            (Weak id)
Variable     | F(  2,   265)  P-val | SW Chi-sq(  2) P-val | SW F(  2,   265)
iAGRI_PF     |      12.62    0.0000 |       25.97   0.0000 |       12.62

NB: first-stage test statistics cluster-robust

Stock-Yogo weak ID F test critical values for single endogenous regressor:
                                   10% maximal IV size             19.93
                                   15% maximal IV size             11.59
                                   20% maximal IV size              8.75
                                   25% maximal IV size              7.25
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for i.i.d. errors only.

Underidentification test
Ho: matrix of reduced form coefficients has rank=K1-1 (underidentified)
Ha: matrix has rank=K1 (identified)
Kleibergen-Paap rk LM statistic          Chi-sq(2)=18.45    P-val=0.0001

Weak identification test
Ho: equation is weakly identified
Cragg-Donald Wald F statistic                                      93.33
Kleibergen-Paap Wald rk F statistic                                12.62

Stock-Yogo weak ID test critical values for K1=1 and L1=2:
                                   10% maximal IV size             19.93
                                   15% maximal IV size             11.59
                                   20% maximal IV size              8.75
                                   25% maximal IV size              7.25
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.

Weak-instrument-robust inference
Tests of joint significance of endogenous regressors B1 in main equation
Ho: B1=0 and orthogonality conditions are valid
Anderson-Rubin Wald test           F(2,265)=       9.20     P-val=0.0001
Anderson-Rubin Wald test           Chi-sq(2)=     18.93     P-val=0.0001
Stock-Wright LM S statistic        Chi-sq(2)=         .     P-val=     .

NB: Underidentification, weak identification and weak-identification-robust
    test statistics cluster-robust

Number of clusters             N_clust  =        266
Number of observations               N  =       2329
Number of regressors                 K  =         56
Number of endogenous regressors      K1 =          1
Number of instruments                L  =         57
Number of excluded instruments       L1 =          2

IV (2SLS) estimation
--------------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on CLIMDIVX

Number of clusters (CLIMDIVX) =    266                Number of obs =     2329
                                                      F( 55,   265) =   215.77
                                                      Prob > F      =   0.0000
Total (centered) SS     =  37.92675517                Centered R2   =   0.1430
Total (uncentered) SS   =   83.7514186                Uncentered R2 =   0.6119
Residual SS             =  32.50176701                Root MSE      =    .1181

-------------------------------------------------------------------------------------
                    |               Robust
ww2_awards_pop40_is |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
           iAGRI_PF |   .0498164   .0120467     4.14   0.000     .0262054    .0734275
         ww1_vol_sh |   .0553424   .0204948     2.70   0.007     .0151734    .0955114
ww1_awards_pop10_is |   .0285471   .0400039     0.71   0.475     -.049859    .1069533
             lpop30 |  -.0091699   .0136692    -0.67   0.502    -.0359609    .0176212
           c30unemp |   .1848281   .1610548     1.15   0.251    -.1308334    .5004896
          c30urban1 |  -.0010635    .006829    -0.16   0.876    -.0144481     .012321
            c30farm |   .0150933   .0291356     0.52   0.604    -.0420114     .072198
            iYf_T29 |   .0009469   .0112717     0.08   0.933    -.0211452     .023039
           MEAN9628 |    -.00058   .0003917    -1.48   0.139    -.0013476    .0001877
             c30men |  -.5457075    .218352    -2.50   0.012    -.9736695   -.1177454
           c30black |  -.0388274   .0231809    -1.67   0.094    -.0842611    .0066063
             c30jap |   .9125856   1.240165     0.74   0.462    -1.518093    3.343264
             c30deu |    .022995   .1282211     0.18   0.858    -.2283137    .2743037
             c30ita |   .0307142   .1949113     0.16   0.875     -.351305    .4127334
             c30vet |   .2290143   .1135767     2.02   0.044      .006408    .4516206
           lc40wage |   .0484989   .0217542     2.23   0.026     .0058614    .0911364
      iwarconpro_PC |   .0045248   .0046085     0.98   0.326    -.0045077    .0135573
      _Istateicps_2 |   .0230224   .0298278     0.77   0.440    -.0354389    .0814838
      _Istateicps_3 |  -.0039094   .0164681    -0.24   0.812    -.0361864    .0283676
      _Istateicps_4 |   .0179834    .029566     0.61   0.543    -.0399648    .0759317
      _Istateicps_5 |   .0703777   .0149184     4.72   0.000     .0411382    .0996171
      _Istateicps_6 |   .0110948   .0367668     0.30   0.763    -.0609667    .0831564
     _Istateicps_11 |  -.0288758   .0182014    -1.59   0.113    -.0645499    .0067983
     _Istateicps_12 |  -.0251916   .0170799    -1.47   0.140    -.0586676    .0082845
     _Istateicps_13 |   .0267126   .0223033     1.20   0.231    -.0170011    .0704264
     _Istateicps_14 |    .007753   .0224968     0.34   0.730    -.0363398    .0518459
     _Istateicps_21 |  -.0605211   .0326552    -1.85   0.064    -.1245242     .003482
     _Istateicps_22 |  -.0707692   .0283983    -2.49   0.013    -.1264288   -.0151096
     _Istateicps_23 |  -.0316894     .03329    -0.95   0.341    -.0969367    .0335579
     _Istateicps_24 |  -.0155027   .0261269    -0.59   0.553    -.0667106    .0357051
     _Istateicps_25 |   -.080549   .0431157    -1.87   0.062    -.1650542    .0039561
     _Istateicps_31 |          0  (omitted)
     _Istateicps_32 |          0  (omitted)
     _Istateicps_33 |          0  (omitted)
     _Istateicps_34 |          0  (omitted)
     _Istateicps_35 |          0  (omitted)
     _Istateicps_36 |          0  (omitted)
     _Istateicps_37 |          0  (omitted)
     _Istateicps_40 |   .0201444   .0253083     0.80   0.426     -.029459    .0697478
     _Istateicps_41 |   -.010327   .0216423    -0.48   0.633    -.0527452    .0320911
     _Istateicps_42 |  -.0229252   .0206729    -1.11   0.267    -.0634432    .0175929
     _Istateicps_43 |   .0438049   .0333798     1.31   0.189    -.0216183    .1092282
     _Istateicps_44 |  -.0231958   .0244545    -0.95   0.343    -.0711257    .0247341
     _Istateicps_45 |   -.011498   .0260181    -0.44   0.659    -.0624926    .0394965
     _Istateicps_46 |   .0360301   .0245366     1.47   0.142    -.0120608     .084121
     _Istateicps_47 |  -.0191988   .0221957    -0.86   0.387    -.0627015    .0243039
     _Istateicps_48 |  -.0094689   .0232445    -0.41   0.684    -.0550272    .0360894
     _Istateicps_49 |   -.016824   .0268583    -0.63   0.531    -.0694654    .0358173
     _Istateicps_51 |  -.0071833   .0249732    -0.29   0.774    -.0561298    .0417632
     _Istateicps_52 |   -.015887   .0316117    -0.50   0.615    -.0778448    .0460709
     _Istateicps_53 |  -.0253997   .0239327    -1.06   0.289     -.072307    .0215076
     _Istateicps_54 |  -.0049765   .0224492    -0.22   0.825    -.0489761     .039023
     _Istateicps_56 |   .0389294   .0263487     1.48   0.140     -.012713    .0905718
     _Istateicps_61 |   .0382295   .0421585     0.91   0.365    -.0443996    .1208586
     _Istateicps_62 |          0  (omitted)
     _Istateicps_63 |  -.0050489    .040205    -0.13   0.900    -.0838492    .0737514
     _Istateicps_64 |   .0830129   .0697495     1.19   0.234    -.0536936    .2197194
     _Istateicps_65 |   .0175391   .0492684     0.36   0.722    -.0790251    .1141032
     _Istateicps_66 |  -.0145873   .0334088    -0.44   0.662    -.0800673    .0508928
     _Istateicps_67 |   .0096059   .0358246     0.27   0.789    -.0606091    .0798208
     _Istateicps_68 |          0  (omitted)
     _Istateicps_71 |   .0437223   .0545754     0.80   0.423    -.0632435     .150688
     _Istateicps_72 |  -.0210778   .0449087    -0.47   0.639    -.1090972    .0669416
     _Istateicps_73 |   .0283128    .033842     0.84   0.403    -.0380164    .0946419
     _Istateicps_98 |          0  (omitted)
              _cons |  -.1432541   .2077433    -0.69   0.490    -.5504236    .2639154
-------------------------------------------------------------------------------------
Underidentification test (Kleibergen-Paap rk LM statistic):             18.451
                                                   Chi-sq(2) P-val =    0.0001
------------------------------------------------------------------------------
Weak identification test (Cragg-Donald Wald F statistic):               93.332
                         (Kleibergen-Paap rk Wald F statistic):         12.625
Stock-Yogo weak ID test critical values: 10% maximal IV size             19.93
                                         15% maximal IV size             11.59
                                         20% maximal IV size              8.75
                                         25% maximal IV size              7.25
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.
------------------------------------------------------------------------------
Warning: estimated covariance matrix of moment conditions not of full rank.
         overidentification statistic not reported, and standard errors and
         model tests should be interpreted with caution.
Possible causes:
         number of clusters insufficient to calculate robust covariance matrix
         singleton dummy variable (dummy with one 1 and N-1 0s or vice versa)
partial option may address problem.
------------------------------------------------------------------------------
Instrumented:         iAGRI_PF
Included instruments: ww1_vol_sh ww1_awards_pop10_is lpop30 c30unemp c30urban1
                      c30farm iYf_T29 MEAN9628 c30men c30black c30jap c30deu
                      c30ita c30vet lc40wage iwarconpro_PC _Istateicps_2
                      _Istateicps_3 _Istateicps_4 _Istateicps_5 _Istateicps_6
                      _Istateicps_11 _Istateicps_12 _Istateicps_13
                      _Istateicps_14 _Istateicps_21 _Istateicps_22
                      _Istateicps_23 _Istateicps_24 _Istateicps_25
                      _Istateicps_40 _Istateicps_41 _Istateicps_42
                      _Istateicps_43 _Istateicps_44 _Istateicps_45
                      _Istateicps_46 _Istateicps_47 _Istateicps_48
                      _Istateicps_49 _Istateicps_51 _Istateicps_52
                      _Istateicps_53 _Istateicps_54 _Istateicps_56
                      _Istateicps_61 _Istateicps_63 _Istateicps_64
                      _Istateicps_65 _Istateicps_66 _Istateicps_67
                      _Istateicps_71 _Istateicps_72 _Istateicps_73
Excluded instruments: iSUM3MO_DROUGHT3340 iAGRI_T73
Dropped collinear:    _Istateicps_31 _Istateicps_32 _Istateicps_33
                      _Istateicps_34 _Istateicps_35 _Istateicps_36
                      _Istateicps_37 _Istateicps_62 _Istateicps_68
                      _Istateicps_98
------------------------------------------------------------------------------
(est8 stored)

. estadd local RA_test = string(`e(arfp)', "%4.3f")

added macro:
            e(RA_test) : "0.000"

.                 qui:   sum  ww2_awards_pop40_is if e(sample) == 1, d

. estadd local y_mean_round = string(r(mean), "%9.3f")

added macro:
       e(y_mean_round) : "0.140"

.        local iqr_y       = (r(p75) - r(p25))

. estadd local IQR_Y = string(`iqr_y', "%9.3f")

added macro:
              e(IQR_Y) : "0.130"

.             qui: sum iAGRI_PF              if e(sample) == 1, d

.        local iqr_x       = (r(p75) - r(p25))*_b[iAGRI_PF]

. estadd local IQR_X = string(`iqr_x', "%9.3f")

added macro:
              e(IQR_X) : "0.055"

.        local iqr_xdY       = (`iqr_x' / `iqr_y')*100

. estadd local IQR_XY = string(`iqr_xdY', "%9.1f") + "\%"

added macro:
             e(IQR_XY) : "42.4\%"

. 
. eststo: xi:  ivreg2 pc1                 (iAGRI_PF = iSUM3MO_DROUGHT3340 iAGRI_T73 ) $control if sample_ols == 1 & servicecommand != 7, cluster
> (CLIMDIVX) first
i.stateicpsr      _Istateicps_1-98    (naturally coded; _Istateicps_1 omitted)
Warning - collinearities detected
Vars dropped:       _Istateicps_31 _Istateicps_32 _Istateicps_33 _Istateicps_34
                    _Istateicps_35 _Istateicps_36 _Istateicps_37 _Istateicps_62
                    _Istateicps_68 _Istateicps_98

First-stage regressions
-----------------------


First-stage regression of iAGRI_PF:

Statistics robust to heteroskedasticity and clustering on CLIMDIVX
Number of obs =                   2329
Number of clusters (CLIMDIVX) =    266
-------------------------------------------------------------------------------------
                    |               Robust
           iAGRI_PF |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
iSUM3MO_DROUGHT3340 |   .3017194   .0620357     4.86   0.000     .1800669     .423372
          iAGRI_T73 |   .2151504   .1027182     2.09   0.036     .0137191    .4165817
         ww1_vol_sh |   .0541683   .0996935     0.54   0.587    -.1413316    .2496681
ww1_awards_pop10_is |      .0621    .178696     0.35   0.728    -.2883244    .4125244
             lpop30 |  -.1977218    .045403    -4.35   0.000    -.2867574   -.1086861
           c30unemp |   -1.11257   .6676518    -1.67   0.096    -2.421841     .196701
          c30urban1 |   .1635703   .0463311     3.53   0.000     .0727146    .2544259
            c30farm |   .0915259   .3156527     0.29   0.772    -.5274718    .7105237
            iYf_T29 |    .341843   .0844944     4.05   0.000     .1761488    .5075372
           MEAN9628 |   .0106535   .0032477     3.28   0.001     .0042847    .0170223
             c30men |  -.3652069    1.86481    -0.20   0.845    -4.022115    3.291701
           c30black |   -.264047   .2875082    -0.92   0.359    -.8278531    .2997591
             c30jap |  -4.334511   5.246493    -0.83   0.409    -14.62293    5.953907
             c30deu |   .6765578   1.035268     0.65   0.513    -1.353611    2.706727
             c30ita |   -1.61388   1.094103    -1.48   0.140    -3.759426    .5316646
             c30vet |   .7112819   .6953677     1.02   0.306    -.6523402    2.074904
           lc40wage |   .0876162   .1586872     0.55   0.581    -.2235707    .3988032
      iwarconpro_PC |   .0034168     .03335     0.10   0.918    -.0619829    .0688165
      _Istateicps_2 |  -1.412081   .3550796    -3.98   0.000    -2.108395   -.7157667
      _Istateicps_3 |  -.0378801   .1325542    -0.29   0.775    -.2978201    .2220599
      _Istateicps_4 |  -1.347562   .1733416    -7.77   0.000    -1.687486   -1.007638
      _Istateicps_5 |  -.3293426   .1130741    -2.91   0.004     -.551082   -.1076033
      _Istateicps_6 |  -.9843088   .2043601    -4.82   0.000    -1.385061   -.5835568
     _Istateicps_11 |  -.4291463   .3273146    -1.31   0.190    -1.071013    .2127205
     _Istateicps_12 |  -.3323729   .1866564    -1.78   0.075    -.6984076    .0336618
     _Istateicps_13 |  -1.199832   .1961727    -6.12   0.000    -1.584529   -.8151361
     _Istateicps_14 |  -1.239489   .1771007    -7.00   0.000    -1.586785   -.8921928
     _Istateicps_21 |  -.2387278   .2920916    -0.82   0.414    -.8115219    .3340663
     _Istateicps_22 |  -.5942314   .2704594    -2.20   0.028    -1.124605   -.0638582
     _Istateicps_23 |   -.849258   .2552081    -3.33   0.001    -1.349723   -.3487926
     _Istateicps_24 |  -.8600766   .2368249    -3.63   0.000    -1.324492   -.3956609
     _Istateicps_25 |  -.5458066   .2935731    -1.86   0.063    -1.121506    .0298927
     _Istateicps_31 |          0  (omitted)
     _Istateicps_32 |          0  (omitted)
     _Istateicps_33 |          0  (omitted)
     _Istateicps_34 |          0  (omitted)
     _Istateicps_35 |          0  (omitted)
     _Istateicps_36 |          0  (omitted)
     _Istateicps_37 |          0  (omitted)
     _Istateicps_40 |  -1.060045    .205751    -5.15   0.000    -1.463524   -.6565654
     _Istateicps_41 |  -.4192332   .2074482    -2.02   0.043     -.826041   -.0124254
     _Istateicps_42 |  -1.069833   .2409245    -4.44   0.000    -1.542288   -.5973781
     _Istateicps_43 |  -.9161689   .2840917    -3.22   0.001    -1.473275   -.3590627
     _Istateicps_44 |  -.3887811   .2208118    -1.76   0.078    -.8217948    .0442327
     _Istateicps_45 |  -.5342521   .3042204    -1.76   0.079    -1.130831    .0623268
     _Istateicps_46 |  -1.144274   .2653921    -4.31   0.000     -1.66471   -.6238378
     _Istateicps_47 |  -.5713226   .2581934    -2.21   0.027    -1.077642   -.0650031
     _Istateicps_48 |   -.646538   .2591545    -2.49   0.013    -1.154742   -.1383339
     _Istateicps_49 |   .0685505   .3198109     0.21   0.830    -.5586015    .6957024
     _Istateicps_51 |  -1.033064   .3703717    -2.79   0.005    -1.759366   -.3067616
     _Istateicps_52 |  -.3209361   .2026502    -1.58   0.113     -.718335    .0764628
     _Istateicps_53 |  -.3890901   .2988818    -1.30   0.193    -.9751999    .1970198
     _Istateicps_54 |  -1.027017    .232123    -4.42   0.000    -1.482213   -.5718221
     _Istateicps_56 |  -1.548947   .2443366    -6.34   0.000    -2.028093   -1.069801
     _Istateicps_61 |  -.7121697   .4108419    -1.73   0.083    -1.517834    .0934948
     _Istateicps_62 |          0  (omitted)
     _Istateicps_63 |  -.4025677   .3355926    -1.20   0.230    -1.060668    .2555323
     _Istateicps_64 |   .2287702   .4423076     0.52   0.605    -.6385989    1.096139
     _Istateicps_65 |  -.6859005   .4379341    -1.57   0.117    -1.544693     .172892
     _Istateicps_66 |  -.2591229   .4164294    -0.62   0.534    -1.075745    .5574987
     _Istateicps_67 |  -.5636995   .3013475    -1.87   0.062    -1.154645    .0272456
     _Istateicps_68 |          0  (omitted)
     _Istateicps_71 |   .3021226   .2625017     1.15   0.250    -.2126456    .8168907
     _Istateicps_72 |  -.4572427   .3564004    -1.28   0.200    -1.156147    .2416616
     _Istateicps_73 |  -.3817661   .3529455    -1.08   0.280    -1.073895     .310363
     _Istateicps_98 |          0  (omitted)
              _cons |   6.394125   1.802429     3.55   0.000     2.859547    9.928704
-------------------------------------------------------------------------------------
F test of excluded instruments:
  F(  2,   265) =    12.62
  Prob > F      =   0.0000
Sanderson-Windmeijer multivariate F test of excluded instruments:
  F(  2,   265) =    12.62
  Prob > F      =   0.0000



Summary results for first-stage regressions
-------------------------------------------

                                           (Underid)            (Weak id)
Variable     | F(  2,   265)  P-val | SW Chi-sq(  2) P-val | SW F(  2,   265)
iAGRI_PF     |      12.62    0.0000 |       25.97   0.0000 |       12.62

NB: first-stage test statistics cluster-robust

Stock-Yogo weak ID F test critical values for single endogenous regressor:
                                   10% maximal IV size             19.93
                                   15% maximal IV size             11.59
                                   20% maximal IV size              8.75
                                   25% maximal IV size              7.25
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for i.i.d. errors only.

Underidentification test
Ho: matrix of reduced form coefficients has rank=K1-1 (underidentified)
Ha: matrix has rank=K1 (identified)
Kleibergen-Paap rk LM statistic          Chi-sq(2)=18.45    P-val=0.0001

Weak identification test
Ho: equation is weakly identified
Cragg-Donald Wald F statistic                                      93.33
Kleibergen-Paap Wald rk F statistic                                12.62

Stock-Yogo weak ID test critical values for K1=1 and L1=2:
                                   10% maximal IV size             19.93
                                   15% maximal IV size             11.59
                                   20% maximal IV size              8.75
                                   25% maximal IV size              7.25
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.

Weak-instrument-robust inference
Tests of joint significance of endogenous regressors B1 in main equation
Ho: B1=0 and orthogonality conditions are valid
Anderson-Rubin Wald test           F(2,265)=      10.08     P-val=0.0001
Anderson-Rubin Wald test           Chi-sq(2)=     20.74     P-val=0.0000
Stock-Wright LM S statistic        Chi-sq(2)=         .     P-val=     .

NB: Underidentification, weak identification and weak-identification-robust
    test statistics cluster-robust

Number of clusters             N_clust  =        266
Number of observations               N  =       2329
Number of regressors                 K  =         56
Number of endogenous regressors      K1 =          1
Number of instruments                L  =         57
Number of excluded instruments       L1 =          2

IV (2SLS) estimation
--------------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on CLIMDIVX

Number of clusters (CLIMDIVX) =    266                Number of obs =     2329
                                                      F( 55,   265) =   167.58
                                                      Prob > F      =   0.0000
Total (centered) SS     =   3677.73843                Centered R2   =   0.5345
Total (uncentered) SS   =  3678.076128                Uncentered R2 =   0.5345
Residual SS             =  1712.017645                Root MSE      =    .8574

-------------------------------------------------------------------------------------
                    |               Robust
                pc1 |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
           iAGRI_PF |   .8247543   .1379337     5.98   0.000     .5544092    1.095099
         ww1_vol_sh |   .4331542     .14217     3.05   0.002     .1545061    .7118024
ww1_awards_pop10_is |   .4680145   .2794755     1.67   0.094    -.0797474    1.015776
             lpop30 |  -.0161675   .0819097    -0.20   0.844    -.1767075    .1443725
           c30unemp |   2.124215   1.124519     1.89   0.059    -.0798026    4.328232
          c30urban1 |   .0072287   .0606176     0.12   0.905    -.1115796     .126037
            c30farm |  -.6426075   .3077149    -2.09   0.037    -1.245718   -.0394974
            iYf_T29 |  -.1318951   .0913459    -1.44   0.149    -.3109297    .0471394
           MEAN9628 |   -.006001   .0033595    -1.79   0.074    -.0125856    .0005836
             c30men |  -6.459359   1.820718    -3.55   0.000     -10.0279   -2.890818
           c30black |  -.9933841   .2358646    -4.21   0.000     -1.45567    -.531098
             c30jap |    11.5459   6.570682     1.76   0.079    -1.332402     24.4242
             c30deu |  -.5917787   .7737676    -0.76   0.444    -2.108335    .9247779
             c30ita |   .1557233   1.390508     0.11   0.911    -2.569622    2.881069
             c30vet |   3.221259   .9113165     3.53   0.000     1.435111    5.007406
           lc40wage |   .9103244   .1714023     5.31   0.000      .574382    1.246267
      iwarconpro_PC |   .2274203   .0462312     4.92   0.000     .1368088    .3180318
      _Istateicps_2 |   .6604316   .3389682     1.95   0.051    -.0039338    1.324797
      _Istateicps_3 |  -.0982863   .2356676    -0.42   0.677    -.5601863    .3636137
      _Istateicps_4 |    1.01629   .2844569     3.57   0.000     .4587643    1.573815
      _Istateicps_5 |   .1302685   .1931385     0.67   0.500     -.248276    .5088131
      _Istateicps_6 |   1.057225   .3504723     3.02   0.003      .370312    1.744138
     _Istateicps_11 |   .0893607   .3209074     0.28   0.781    -.5396062    .7183276
     _Istateicps_12 |    -.17893    .221375    -0.81   0.419     -.612817     .254957
     _Istateicps_13 |    .631846    .265768     2.38   0.017     .1109504    1.152742
     _Istateicps_14 |   .2723731   .2527832     1.08   0.281    -.2230728    .7678191
     _Istateicps_21 |  -.2979324   .2775472    -1.07   0.283     -.841915    .2460502
     _Istateicps_22 |  -.4297302   .2662337    -1.61   0.107    -.9515388    .0920783
     _Istateicps_23 |  -.0645534   .2976112    -0.22   0.828    -.6478607    .5187538
     _Istateicps_24 |  -.1205424   .2487316    -0.48   0.628    -.6080474    .3669627
     _Istateicps_25 |   -.028747   .3177108    -0.09   0.928    -.6514487    .5939547
     _Istateicps_31 |          0  (omitted)
     _Istateicps_32 |          0  (omitted)
     _Istateicps_33 |          0  (omitted)
     _Istateicps_34 |          0  (omitted)
     _Istateicps_35 |          0  (omitted)
     _Istateicps_36 |          0  (omitted)
     _Istateicps_37 |          0  (omitted)
     _Istateicps_40 |   .4322081   .2819023     1.53   0.125    -.1203102    .9847264
     _Istateicps_41 |    .366587    .254237     1.44   0.149    -.1317085    .8648824
     _Istateicps_42 |  -.5466495   .2416847    -2.26   0.024    -1.020343   -.0729561
     _Istateicps_43 |   .9528217   .2902698     3.28   0.001     .3839034     1.52174
     _Istateicps_44 |   .2408232   .2631935     0.92   0.360    -.2750265     .756673
     _Istateicps_45 |  -.3362653    .295716    -1.14   0.255     -.915858    .2433274
     _Istateicps_46 |   .7896323   .2820737     2.80   0.005      .236778    1.342487
     _Istateicps_47 |   .0953308   .3071012     0.31   0.756    -.5065765    .6972381
     _Istateicps_48 |  -.1003774   .2644848    -0.38   0.704     -.618758    .4180032
     _Istateicps_49 |   .7054391   .3010982     2.34   0.019     .1152976    1.295581
     _Istateicps_51 |   .1449329   .3026981     0.48   0.632    -.4483445    .7382103
     _Istateicps_52 |  -.4490972   .3014397    -1.49   0.136    -1.039908    .1417137
     _Istateicps_53 |   .1314527   .2728939     0.48   0.630    -.4034094    .6663149
     _Istateicps_54 |   .1602319    .269326     0.59   0.552    -.3676374    .6881011
     _Istateicps_56 |   .9468981   .3361389     2.82   0.005     .2880779    1.605718
     _Istateicps_61 |  -.4796931    .359161    -1.34   0.182    -1.183636    .2242494
     _Istateicps_62 |          0  (omitted)
     _Istateicps_63 |  -.0920944   .3141694    -0.29   0.769    -.7078551    .5236662
     _Istateicps_64 |   .7938474   .4190806     1.89   0.058    -.0275355     1.61523
     _Istateicps_65 |   .0394076   .3571554     0.11   0.912    -.6606042    .7394194
     _Istateicps_66 |  -.1508506   .2858043    -0.53   0.598    -.7110167    .4093155
     _Istateicps_67 |  -.3625599   .2819849    -1.29   0.199    -.9152402    .1901205
     _Istateicps_68 |          0  (omitted)
     _Istateicps_71 |   .0688688   .3653861     0.19   0.850    -.6472747    .7850123
     _Istateicps_72 |   .0684012   .3434492     0.20   0.842    -.6047468    .7415492
     _Istateicps_73 |   .6408049    .282687     2.27   0.023     .0867487    1.194861
     _Istateicps_98 |          0  (omitted)
              _cons |  -7.410705   2.137372    -3.47   0.001    -11.59988   -3.221534
-------------------------------------------------------------------------------------
Underidentification test (Kleibergen-Paap rk LM statistic):             18.451
                                                   Chi-sq(2) P-val =    0.0001
------------------------------------------------------------------------------
Weak identification test (Cragg-Donald Wald F statistic):               93.332
                         (Kleibergen-Paap rk Wald F statistic):         12.625
Stock-Yogo weak ID test critical values: 10% maximal IV size             19.93
                                         15% maximal IV size             11.59
                                         20% maximal IV size              8.75
                                         25% maximal IV size              7.25
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.
------------------------------------------------------------------------------
Warning: estimated covariance matrix of moment conditions not of full rank.
         overidentification statistic not reported, and standard errors and
         model tests should be interpreted with caution.
Possible causes:
         number of clusters insufficient to calculate robust covariance matrix
         singleton dummy variable (dummy with one 1 and N-1 0s or vice versa)
partial option may address problem.
------------------------------------------------------------------------------
Instrumented:         iAGRI_PF
Included instruments: ww1_vol_sh ww1_awards_pop10_is lpop30 c30unemp c30urban1
                      c30farm iYf_T29 MEAN9628 c30men c30black c30jap c30deu
                      c30ita c30vet lc40wage iwarconpro_PC _Istateicps_2
                      _Istateicps_3 _Istateicps_4 _Istateicps_5 _Istateicps_6
                      _Istateicps_11 _Istateicps_12 _Istateicps_13
                      _Istateicps_14 _Istateicps_21 _Istateicps_22
                      _Istateicps_23 _Istateicps_24 _Istateicps_25
                      _Istateicps_40 _Istateicps_41 _Istateicps_42
                      _Istateicps_43 _Istateicps_44 _Istateicps_45
                      _Istateicps_46 _Istateicps_47 _Istateicps_48
                      _Istateicps_49 _Istateicps_51 _Istateicps_52
                      _Istateicps_53 _Istateicps_54 _Istateicps_56
                      _Istateicps_61 _Istateicps_63 _Istateicps_64
                      _Istateicps_65 _Istateicps_66 _Istateicps_67
                      _Istateicps_71 _Istateicps_72 _Istateicps_73
Excluded instruments: iSUM3MO_DROUGHT3340 iAGRI_T73
Dropped collinear:    _Istateicps_31 _Istateicps_32 _Istateicps_33
                      _Istateicps_34 _Istateicps_35 _Istateicps_36
                      _Istateicps_37 _Istateicps_62 _Istateicps_68
                      _Istateicps_98
------------------------------------------------------------------------------
(est9 stored)

. estadd local RA_test = string(`e(arfp)', "%4.3f")

added macro:
            e(RA_test) : "0.000"

.                 qui:   sum  pc1                if e(sample) == 1, d

. estadd local y_mean_round = string(r(mean), "%9.3f")

added macro:
       e(y_mean_round) : "-0.012"

.        local iqr_y       = (r(p75) - r(p25))

. estadd local IQR_Y = string(`iqr_y', "%9.3f")

added macro:
              e(IQR_Y) : "1.658"

.             qui: sum iAGRI_PF              if e(sample) == 1, d

.        local iqr_x       = (r(p75) - r(p25))*_b[iAGRI_PF]

. estadd local IQR_X = string(`iqr_x', "%9.3f")

added macro:
              e(IQR_X) : "0.915"

.        local iqr_xdY       = (`iqr_x' / `iqr_y')*100

. estadd local IQR_XY = string(`iqr_xdY', "%9.1f") + "\%"

added macro:
             e(IQR_XY) : "55.2\%"

. 
. esttab using "results/tables/Tab4-id-summary.tex" ,  ///
> indicate("County controls = $control_nofe" "State FE (48) = *state*")                                                                      ///
>         keep(iAGRI_PF iSUM3MO_DROUGHT3340 iAGRI_T73 ) order(iAGRI_PF iSUM3MO_DROUGHT3340 iAGRI_T73)                                    ///
>         mgroups("Agri support" "War bonds" "Volunteers" "Medals" "PCA" "War bonds" "Volunteers" "Medals" "PCA", pattern(1 1 1 1 1 1 1 1 1) ///
>                         prefix(\multicolumn{@span}{c}{) suffix(})                                                                             
>  ///
>                         span erepeat(\cmidrule(lr){@span}) )                                                                                  
>          ///
>         mlabel("FS" "RF" "RF" "RF" "RF" "2SLS" "2SLS" "2SLS" "2SLS")                                                                       ///
>         scalars("F_test F-test of excluded instrument" "y_mean_round Mean dependent variable" "IQR_X Agri support IQR $\times$ $\beta$" "IQR_X
> Y Agri support IQR $\times$ $\beta$ / IQR dep. var." "RA_test Rubin-Anderson test (p-value)") ///
>         replace br se  label star(* 0.10 ** 0.05 *** 0.01) obslast nomtitles  compress longtable                                           ///
>         b(%9.3f) se(%9.3f) r2(%9.3f)        nonotes                                                                                           
> ///
>         nogaps title("Identification: instruments are 1933-40 droughts and tenure in the agri committee.") 
(output written to results/tables/Tab4-id-summary.tex)

.         
. ***************************************************************************************************
. ****         Tab 5. Identification: Individual level                                                   ****
. ***************************************************************************************************
. 
. ***************************************************************************************************
. ****              a. Cols. 2 + 4                                                                                       ****
. ***************************************************************************************************
. 
. use "tmp/asn", clear

. 
. qui reghdfe vol  iAAA_PF_farmer iAAA_PF_farmhand                                   farmer farmhand $controls_asn, absorb(countyn)

. gen insample = e(sample) == 1

. 
. estimates clear

. eststo: xi:    reghdfe  vol  iSUM3MO_DROUGHT3340_farmer iAGRI_T73_farmer iSUM3MO_DROUGHT3340_farmhand iAGRI_T73_farmhand farmer farmhand $cont
> rols_asn if insample == 1, cluster(countyn) absorb(countyn)
i.C40AGE          _IC40AGE_11-40      (naturally coded; _IC40AGE_11 omitted)
(MWFE estimator converged in 1 iterations)
note: C40SCHOOL_C omitted because of collinearity

HDFE Linear regression                            Number of obs   =    463,248
Absorbing 1 HDFE group                            F(  43,   2314) =     195.20
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.1442
                                                  Adj R-squared   =     0.1399
                                                  Within R-sq.    =     0.0823
Number of clusters (countyn) =      2,315         Root MSE        =     0.3287

                                            (Std. Err. adjusted for 2,315 clusters in countyn)
----------------------------------------------------------------------------------------------
                             |               Robust
                   volunteer |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------------------+----------------------------------------------------------------
  iSUM3MO_DROUGHT3340_farmer |   14.45344   4.556888     3.17   0.002     5.517424    23.38945
            iAGRI_T73_farmer |   32.47944   10.54866     3.08   0.002     11.79363    53.16526
iSUM3MO_DROUGHT3340_farmhand |  -21.07905   4.127116    -5.11   0.000    -29.17228   -12.98582
          iAGRI_T73_farmhand |  -8.260906   8.792057    -0.94   0.348    -25.50204    8.980227
                      farmer |   -.084794    .008799    -9.64   0.000    -.1020486   -.0675393
                    farmhand |  -.0020604   .0082008    -0.25   0.802    -.0181421    .0140212
                           h |   .3820628   .0475796     8.03   0.000     .2887597     .475366
                           w |  -.0027355   .0005872    -4.66   0.000     -.003887    -.001584
                         bmi |    .003193   .0017395     1.84   0.067    -.0002181    .0066041
                 C40NONWHITE |   -.116284   .0029621   -39.26   0.000    -.1220926   -.1104754
                  C40MARRIED |  -.0510053   .0018943   -26.93   0.000    -.0547201   -.0472905
                  noncitizen |  -.0708373     .00698   -10.15   0.000     -.084525   -.0571496
                 C40SCHOOL_E |  -.1382022   .0044624   -30.97   0.000    -.1469529   -.1294515
                 C40SCHOOL_H |  -.0508883   .0045929   -11.08   0.000    -.0598949   -.0418818
                 C40SCHOOL_C |          0  (omitted)
                 _IC40AGE_12 |   .0500433   .0531515     0.94   0.347    -.0541861    .1542728
                 _IC40AGE_13 |  -.0131992   .0503602    -0.26   0.793    -.1119551    .0855566
                 _IC40AGE_14 |   .0059883   .0503866     0.12   0.905    -.0928192    .1047959
                 _IC40AGE_15 |  -.0413826   .0501598    -0.83   0.409    -.1397455    .0569803
                 _IC40AGE_16 |   .2017179   .0504578     4.00   0.000     .1027707    .3006651
                 _IC40AGE_17 |   .1398887   .0500647     2.79   0.005     .0417124    .2380649
                 _IC40AGE_18 |   .1267045     .04982     2.54   0.011     .0290079     .224401
                 _IC40AGE_19 |   .0725193   .0497254     1.46   0.145    -.0249917    .1700304
                 _IC40AGE_20 |    .071627   .0497802     1.44   0.150    -.0259915    .1692455
                 _IC40AGE_21 |   .0520616   .0497269     1.05   0.295    -.0454524    .1495755
                 _IC40AGE_22 |   .0376928   .0497022     0.76   0.448    -.0597727    .1351584
                 _IC40AGE_23 |   .0266519   .0496844     0.54   0.592    -.0707787    .1240824
                 _IC40AGE_24 |   .0203069   .0497033     0.41   0.683    -.0771607    .1177745
                 _IC40AGE_25 |   .0132801   .0497827     0.27   0.790    -.0843432    .1109034
                 _IC40AGE_26 |  -.0036299    .049736    -0.07   0.942    -.1011616    .0939018
                 _IC40AGE_27 |  -.0097666   .0496983    -0.20   0.844    -.1072245    .0876913
                 _IC40AGE_28 |  -.0127403   .0497672    -0.26   0.798    -.1103333    .0848528
                 _IC40AGE_29 |  -.0205176   .0497481    -0.41   0.680    -.1180732     .077038
                 _IC40AGE_30 |   -.018017   .0497404    -0.36   0.717    -.1155574    .0795234
                 _IC40AGE_31 |   -.017426   .0498789    -0.35   0.727    -.1152381     .080386
                 _IC40AGE_32 |   -.022919   .0498096    -0.46   0.645    -.1205952    .0747572
                 _IC40AGE_33 |   -.033972   .0497616    -0.68   0.495    -.1315541    .0636101
                 _IC40AGE_34 |  -.0410375   .0498434    -0.82   0.410    -.1387798    .0567049
                 _IC40AGE_35 |  -.0468813   .0497945    -0.94   0.347    -.1445279    .0507652
                 _IC40AGE_36 |  -.0387444   .0498575    -0.78   0.437    -.1365144    .0590257
                 _IC40AGE_37 |   -.028365   .0498495    -0.57   0.569    -.1261193    .0693894
                 _IC40AGE_38 |  -.0299812   .0498387    -0.60   0.548    -.1277143    .0677519
                 _IC40AGE_39 |   -.038918   .0498586    -0.78   0.435    -.1366901    .0588541
                 _IC40AGE_40 |  -.0395922   .0497848    -0.80   0.427    -.1372197    .0580353
                       _cons |   -.285751   .0965056    -2.96   0.003    -.4749975   -.0965045
----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     countyn |      2315        2315           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est1 stored)

.        qui:    sum  vol if e(sample) == 1

.         estadd local y_mean_round = string(r(mean), "%9.3f")

added macro:
       e(y_mean_round) : "0.147"

.         estadd local fe           = "Yes"

added macro:
                 e(fe) : "Yes"

.         estadd local sample       = "Army"

added macro:
             e(sample) : "Army"

.         
. eststo: xi:  ivreghdfe vol (iAAA_PF_farmer iAAA_PF_farmhand  = iSUM3MO_DROUGHT3340_farmer iAGRI_T73_farmer iSUM3MO_DROUGHT3340_farmhand iAGRI_
> T73_farmhand) farmer farmhand $controls_asn  if insample == 1, cluster(countyn) absorb(countyn)
i.C40AGE          _IC40AGE_11-40      (naturally coded; _IC40AGE_11 omitted)
(MWFE estimator converged in 1 iterations)

IV (2SLS) estimation
--------------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on countyn

Number of clusters (countyn) =    2315                Number of obs =   463248
                                                      F( 41,  2314) =   196.65
                                                      Prob > F      =   0.0000
Total (centered) SS     =   54252.5716                Centered R2   =   0.0651
Total (uncentered) SS   =   54252.5716                Uncentered R2 =   0.0651
Residual SS             =  50721.34503                Root MSE      =    .3309

----------------------------------------------------------------------------------
                 |               Robust
       volunteer |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------+----------------------------------------------------------------
  iAAA_PF_farmer |   76.99998   13.08395     5.89   0.000      51.3425    102.6575
iAAA_PF_farmhand |  -57.70958    10.0862    -5.72   0.000    -77.48852   -37.93064
          farmer |   -.518693   .0750802    -6.91   0.000    -.6659244   -.3714616
        farmhand |   .2946044   .0566106     5.20   0.000     .1835917    .4056172
               h |   .3757695   .0484225     7.76   0.000     .2808134    .4707255
               w |  -.0026575   .0005974    -4.45   0.000     -.003829    -.001486
             bmi |   .0028816    .001774     1.62   0.104    -.0005971    .0063604
     C40NONWHITE |  -.1146614   .0030463   -37.64   0.000    -.1206352   -.1086876
      C40MARRIED |  -.0526091   .0019445   -27.05   0.000    -.0564223   -.0487959
      noncitizen |  -.0708606   .0078142    -9.07   0.000    -.0861841    -.055537
     C40SCHOOL_E |  -.0860683   .0019268   -44.67   0.000    -.0898467   -.0822899
     C40SCHOOL_H |          0  (omitted)
     C40SCHOOL_C |   .0506969   .0046189    10.98   0.000     .0416393    .0597544
     _IC40AGE_12 |   .0409412   .0531053     0.77   0.441    -.0631978    .1450802
     _IC40AGE_13 |   -.019269   .0499623    -0.39   0.700    -.1172445    .0787065
     _IC40AGE_14 |  -.0011711   .0501069    -0.02   0.981    -.0994303    .0970881
     _IC40AGE_15 |  -.0506515   .0497737    -1.02   0.309    -.1482572    .0469542
     _IC40AGE_16 |   .1969315   .0500816     3.93   0.000     .0987221    .2951409
     _IC40AGE_17 |    .133433   .0495504     2.69   0.007     .0362652    .2306008
     _IC40AGE_18 |    .120013   .0493247     2.43   0.015     .0232878    .2167383
     _IC40AGE_19 |   .0663169    .049251     1.35   0.178    -.0302637    .1628976
     _IC40AGE_20 |   .0664084    .049306     1.35   0.178    -.0302801    .1630969
     _IC40AGE_21 |   .0463079   .0493042     0.94   0.348    -.0503771     .142993
     _IC40AGE_22 |   .0323711   .0492617     0.66   0.511    -.0642306    .1289727
     _IC40AGE_23 |   .0211662   .0492524     0.43   0.667    -.0754172    .1177496
     _IC40AGE_24 |   .0151103   .0492846     0.31   0.759    -.0815362    .1117568
     _IC40AGE_25 |    .008041   .0493508     0.16   0.871    -.0887353    .1048173
     _IC40AGE_26 |  -.0081681   .0493292    -0.17   0.868    -.1049023     .088566
     _IC40AGE_27 |  -.0150426   .0492552    -0.31   0.760    -.1116315    .0815463
     _IC40AGE_28 |  -.0175323   .0493353    -0.36   0.722    -.1142783    .0792137
     _IC40AGE_29 |  -.0258778   .0493627    -0.52   0.600    -.1226775    .0709219
     _IC40AGE_30 |  -.0230748   .0493168    -0.47   0.640    -.1197845    .0736349
     _IC40AGE_31 |  -.0229126   .0494428    -0.46   0.643    -.1198694    .0740441
     _IC40AGE_32 |  -.0263387   .0493443    -0.53   0.594    -.1231023    .0704249
     _IC40AGE_33 |  -.0388928   .0493479    -0.79   0.431    -.1356634    .0578779
     _IC40AGE_34 |  -.0439943   .0493983    -0.89   0.373    -.1408637    .0528752
     _IC40AGE_35 |  -.0514048   .0493728    -1.04   0.298    -.1482244    .0454148
     _IC40AGE_36 |  -.0426433   .0494217    -0.86   0.388    -.1395587    .0542722
     _IC40AGE_37 |  -.0327617   .0494065    -0.66   0.507    -.1296473    .0641239
     _IC40AGE_38 |   -.034836    .049422    -0.70   0.481    -.1317521      .06208
     _IC40AGE_39 |  -.0427861   .0494411    -0.87   0.387    -.1397397    .0541675
     _IC40AGE_40 |  -.0423727   .0493737    -0.86   0.391    -.1391939    .0544486
----------------------------------------------------------------------------------
Underidentification test (Kleibergen-Paap rk LM statistic):            183.843
                                                   Chi-sq(3) P-val =    0.0000
------------------------------------------------------------------------------
Weak identification test (Cragg-Donald Wald F statistic):              1.4e+04
                         (Kleibergen-Paap rk Wald F statistic):         49.271
Stock-Yogo weak ID test critical values:  5% maximal IV relative bias    11.04
                                         10% maximal IV relative bias     7.56
                                         20% maximal IV relative bias     5.57
                                         30% maximal IV relative bias     4.73
                                         10% maximal IV size             16.87
                                         15% maximal IV size              9.93
                                         20% maximal IV size              7.54
                                         25% maximal IV size              6.28
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.
------------------------------------------------------------------------------
Warning: estimated covariance matrix of moment conditions not of full rank.
         overidentification statistic not reported, and standard errors and
         model tests should be interpreted with caution.
Possible causes:
         number of clusters insufficient to calculate robust covariance matrix
         singleton dummy variable (dummy with one 1 and N-1 0s or vice versa)
partial option may address problem.
------------------------------------------------------------------------------
Collinearities detected among instruments: 1 instrument(s) dropped
Instrumented:         iAAA_PF_farmer iAAA_PF_farmhand
Included instruments: farmer farmhand h w bmi C40NONWHITE C40MARRIED noncitizen
                      C40SCHOOL_E C40SCHOOL_H C40SCHOOL_C _IC40AGE_12
                      _IC40AGE_13 _IC40AGE_14 _IC40AGE_15 _IC40AGE_16
                      _IC40AGE_17 _IC40AGE_18 _IC40AGE_19 _IC40AGE_20
                      _IC40AGE_21 _IC40AGE_22 _IC40AGE_23 _IC40AGE_24
                      _IC40AGE_25 _IC40AGE_26 _IC40AGE_27 _IC40AGE_28
                      _IC40AGE_29 _IC40AGE_30 _IC40AGE_31 _IC40AGE_32
                      _IC40AGE_33 _IC40AGE_34 _IC40AGE_35 _IC40AGE_36
                      _IC40AGE_37 _IC40AGE_38 _IC40AGE_39 _IC40AGE_40
Excluded instruments: iSUM3MO_DROUGHT3340_farmer iAGRI_T73_farmer
                      iSUM3MO_DROUGHT3340_farmhand iAGRI_T73_farmhand
Partialled-out:       _cons
                      nb: total SS, model F and R2s are after partialling-out;
                          any small-sample adjustments include partialled-out
                          variables in regressor count K
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
     countyn |      2315        2315           0    *|
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation
(est2 stored)

.        qui:    sum  vol if e(sample) == 1

.         estadd local y_mean_round = string(r(mean), "%9.3f")

added macro:
       e(y_mean_round) : "0.147"

.         estadd local fe           = "Yes"

added macro:
                 e(fe) : "Yes"

.         estadd local sample       = "Army"

added macro:
             e(sample) : "Army"

.         
. esttab using "results/tables/Tab5-id-b.tex" ,                                                             ///
> indicate("Age FEs = *AGE*" "Individual controls (military) = $controls_asn_noage")                                                ///
>                 order(iAAA_PF_farmer iAAA_PF_farmhand iSUM3MO_DROUGHT3340_farmer iAGRI_T73_farmer iSUM3MO_DROUGHT3340_farmhand iAGRI_T73_farmh
> and farmer farmhand)  ///
>                 mgroups("Volunteer" , pattern(1 0)                                                                                            
>                             ///
>                 prefix(\multicolumn{@span}{c}{) suffix(})                                                         ///
>                         span erepeat(\cmidrule(lr){@span}) )                                                                              ///
>                 mlabel("RF" "2SLS" )                                                                                              ///
>         scalars("fe County FEs" "y_mean_round Mean dependent variable" "sample Sample:")                                  ///
>         replace br se  label star(* 0.10 ** 0.05 *** 0.01) obslast nomtitles nonum compress                   ///
>         b(%9.3f) se(%9.3f) r2(%9.3f) nonotes                                                                         ///
>         nogaps title("Identification Table: Individual-Level.")
(output written to results/tables/Tab5-id-b.tex)

.         
. 
. ***************************************************************************************************
. ****     II. Figures                                                                           ****
. ***************************************************************************************************
. 
. ***************************************************************************************************
. ****         Fig 1. New Deal Spending and WW II Patriotism                                                 ****
. ***************************************************************************************************
. 
. use "tmp/patriot", clear

. 
. preserve

.         keep if sample_ols == 1 & iwarbond_1944_PC != . & iNDEXP_PC != . & ww1_vol_sh != . & ww1_awards_pop10_is != .
(48 observations deleted)

.         reg iwarbond_1944_PC ww1_vol_sh ww1_awards_pop10_is 

      Source |       SS           df       MS      Number of obs   =     3,022
-------------+----------------------------------   F(2, 3019)      =    125.80
       Model |  106.254929         2  53.1274646   Prob > F        =    0.0000
    Residual |  1274.99699     3,019  .422324276   R-squared       =    0.0769
-------------+----------------------------------   Adj R-squared   =    0.0763
       Total |  1381.25192     3,021  .457216789   Root MSE        =    .64986

-------------------------------------------------------------------------------------
   iwarbond_1944_PC |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
         ww1_vol_sh |   .5955832   .0469426    12.69   0.000     .5035405    .6876259
ww1_awards_pop10_is |   1.089459   .1291976     8.43   0.000     .8361345    1.342783
              _cons |   4.385218    .021185   207.00   0.000     4.343679    4.426756
-------------------------------------------------------------------------------------

.         predict e, resid

.         xtile iNDEXP_PC_50 = iNDEXP_PC , n(50)

.         collapse (mean) e iNDEXP_PC , by(iNDEXP_PC_50)

.         twoway (scatter e                iNDEXP_PC , mfcolor(none) mlcolor(black)) ///
>                    (lfit    e                iNDEXP_PC , lcolor(red)                 ), ylabel( , format(%2.1f) labsize(large) angle(0) grid) 
> legend(off) xlabel(4 "4" 5 "5" 6 "6" 7 "7", grid labsize(large)) xtitle(log New Deal $ p.c., size(large)) ytitle(, size(large)) title(A. War b
> onds, size(huge))  name(g1, replace) plotregion(fcolor(white)) graphregion(fcolor(white)) scheme(s1manual) 

. restore

. 
. preserve

.         keep if sample_ols == 1 & ww2_vol_pop40 != . & iNDEXP_PC != . & servicecommand != 7 & ww1_vol_sh != . & ww1_awards_pop10_is != .
(741 observations deleted)

.         reg ww2_vol_pop40 ww1_vol_sh ww1_awards_pop10_is 

      Source |       SS           df       MS      Number of obs   =     2,329
-------------+----------------------------------   F(2, 2326)      =     39.11
       Model |  8.84626729         2  4.42313364   Prob > F        =    0.0000
    Residual |  263.091202     2,326  .113108857   R-squared       =    0.0325
-------------+----------------------------------   Adj R-squared   =    0.0317
       Total |  271.937469     2,328  .116811628   Root MSE        =    .33632

-------------------------------------------------------------------------------------
      ww2_vol_pop40 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
         ww1_vol_sh |   .1846437   .0287572     6.42   0.000     .1282513    .2410361
ww1_awards_pop10_is |   .4146666    .075391     5.50   0.000     .2668262    .5625071
              _cons |   .5477097   .0124206    44.10   0.000     .5233532    .5720662
-------------------------------------------------------------------------------------

.         predict e, resid

.         xtile iNDEXP_PC_50 = iNDEXP_PC , n(50)

.         collapse (mean) e iNDEXP_PC , by(iNDEXP_PC_50)

.         twoway (scatter e iNDEXP_PC , mfcolor(none) mlcolor(black)) ///
>                    (lfit    e iNDEXP_PC , lcolor(red)                 ), ylabel( , format(%3.2f) labsize(large) angle(0) grid) legend(off) xla
> bel(4 "4" 5 "5" 6 "6" 7 "7", grid labsize(large)) xtitle(log New Deal $ p.c., size(large)) ytitle(, size(large)) title(B. Volunteers, size(hug
> e)) name(g2, replace) plotregion(fcolor(white)) graphregion(fcolor(white)) scheme(s1manual) 

. restore

. 
. preserve

.         keep if sample_ols == 1 & ww2_awards_pop40_is != . & iNDEXP_PC != . & servicecommand != 7 & ww1_vol_sh != . & ww1_awards_pop10_is != .
(741 observations deleted)

.         reg ww2_vol_pop40 ww1_vol_sh ww1_awards_pop10_is 

      Source |       SS           df       MS      Number of obs   =     2,329
-------------+----------------------------------   F(2, 2326)      =     39.11
       Model |  8.84626729         2  4.42313364   Prob > F        =    0.0000
    Residual |  263.091202     2,326  .113108857   R-squared       =    0.0325
-------------+----------------------------------   Adj R-squared   =    0.0317
       Total |  271.937469     2,328  .116811628   Root MSE        =    .33632

-------------------------------------------------------------------------------------
      ww2_vol_pop40 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
         ww1_vol_sh |   .1846437   .0287572     6.42   0.000     .1282513    .2410361
ww1_awards_pop10_is |   .4146666    .075391     5.50   0.000     .2668262    .5625071
              _cons |   .5477097   .0124206    44.10   0.000     .5233532    .5720662
-------------------------------------------------------------------------------------

.         predict e, resid

.         xtile iNDEXP_PC_50 = iNDEXP_PC , n(50)

.         collapse (mean) e iNDEXP_PC , by(iNDEXP_PC_50)

.         twoway (scatter e iNDEXP_PC , mfcolor(none) mlcolor(black)) ///
>                    (lfit    e iNDEXP_PC , lcolor(red)                 ), ylabel( , format(%2.1f) labsize(large) angle(0) grid) legend(off) xla
> bel(4 "4" 5 "5" 6 "6" 7 "7", grid labsize(large)) xtitle(log New Deal $ p.c., size(large)) ytitle(, size(large)) title(C. Medals, size(huge)) 
>  name(g3, replace) plotregion(fcolor(white)) graphregion(fcolor(white)) scheme(s1manual) 

. restore

. 
. graph combine g1 g2 g3, r(1) plotregion(fcolor(white)) graphregion(fcolor(white)) scheme(s1manual) 

. graph drop    g1 g2 g3

. graph export "results/figures/Fig1_main.pdf", replace as(pdf)
(file results/figures/Fig1_main.pdf written in PDF format)

. graph export "results/figures/Fig1_main.png", replace as(png)
(file results/figures/Fig1_main.png written in PNG format)

. 
. ***************************************************************************************************
. ****         Fig 2. Geographic Distribution of Main Variables                                          ****
. ***************************************************************************************************
. format iwarbond_1944_PC ww2_vol_pop40    ww2_awards_pop40_is iNDEXP_PC iAGRI_PF %2.1f

. format iAGRI_PF iSUM3MO_DROUGHT3340 %2.1f

. ren _ID_CA _ID

. ***************************************************************************************************
. ****              a. War bonds                                                                             ****
. ***************************************************************************************************
. spmap  iwarbond_1944_PC using data/C-CountiesND_CA, id(_ID) fcolor(Blues2) clnumber(9) ndocolor(none) ocolor(none ..)                 ///
>                legend( position(5) bplacement(sw) r(5))                                                                                   ///
>                         line(data(data/C-USA_CA)) title(A. War bonds, size(*1.4))

. graph export "results/figures/Fig2A_map-bonds.png", as(png) replace
(file results/figures/Fig2A_map-bonds.png written in PNG format)

. graph export "results/figures/Fig2A_map-bonds.pdf", as(pdf) replace
(file results/figures/Fig2A_map-bonds.pdf written in PDF format)

.                                                 
. ***************************************************************************************************
. ****              b. Volunteers                                                                ****
. ***************************************************************************************************
. spmap  ww2_vol_pop40          using data/C-CountiesND_CA, id(_ID) fcolor(Blues2) clnumber(9) ndocolor(none) ocolor(none ..)       ///
>                legend( position(5) bplacement(sw) r(5))                                                                           ///
>                         polygon(data(data/C-ServiceCommand7) osize(vthick)) line(data(data/C-USA_CA)) title(B. Volunteers, size(*1.4)) 

. graph export "results/figures/Fig2B_map-volunteers.png", as(png) replace
(file results/figures/Fig2B_map-volunteers.png written in PNG format)

. graph export "results/figures/Fig2B_map-volunteers.pdf", as(pdf) replace
(file results/figures/Fig2B_map-volunteers.pdf written in PDF format)

. 
. ***************************************************************************************************
. ****              c. Medals                                                                                ****
. ***************************************************************************************************
. spmap  ww2_awards_pop40_is using data/C-CountiesND_CA, id(_ID) fcolor(Blues2) clnumber(9) ndocolor(none) ocolor(none ..)                ///
>                legend( position(5) bplacement(sw) r(5))                                                                         ///
>                         polygon(data(data/C-ServiceCommand7) osize(vthick)) line(data(data/C-USA_CA)) title(C. Medals, size(*1.4))

. graph export "results/figures/Fig2C_map-medals.png", as(png) replace
(file results/figures/Fig2C_map-medals.png written in PNG format)

. graph export "results/figures/Fig2C_map-medals.pdf", as(pdf) replace
(file results/figures/Fig2C_map-medals.pdf written in PDF format)

. 
. ***************************************************************************************************
. ****              d. New Deal grants                                                                   ****
. ***************************************************************************************************
. spmap  iNDEXP_PC        using data/C-CountiesND_CA, id(_ID) fcolor(Reds2) clnumber(9) ndocolor(none) ocolor(none ..)                     ///
>                legend( position(5) bplacement(sw) r(5))                                                                          ///
>                         line(data(data/C-USA_CA)) title(D. New Deal grants, size(*1.4))

. graph export "results/figures/Fig2D_map-grants.png", as(png) replace
(file results/figures/Fig2D_map-grants.png written in PNG format)

. graph export "results/figures/Fig2D_map-grants.pdf", as(pdf) replace
(file results/figures/Fig2D_map-grants.pdf written in PDF format)

. 
. ***************************************************************************************************
. ****              e. Agricultural support                                                                  ****
. ***************************************************************************************************
. 
. spmap  iAGRI_PF            using data/C-CountiesND_CA, id(_ID) fcolor(Greens2) clnumber(9) ndocolor(none) ocolor(none ..)  ///
>                legend( position(5) bplacement(sw) r(5))                                                                          ///
>                         line(data(data/C-USA_CA)) title(E. Agricultural support, size(*1.4))

. graph export "results/figures/Fig2E_map-aaa.png", as(png) replace
(file results/figures/Fig2E_map-aaa.png written in PNG format)

. graph export "results/figures/Fig2E_map-aaa.pdf", as(pdf) replace
(file results/figures/Fig2E_map-aaa.pdf written in PDF format)

.                                                 
. ***************************************************************************************************
. ****              f. Droughts                                                                              ****
. ***************************************************************************************************
. spmap  iSUM3MO_DROUGHT3340 using data/C-CountiesND_CA, id(_ID) fcolor(Greys2) clnumber(9) ndocolor(none) ocolor(none ..)  ///
>                legend( position(5) bplacement(sw) r(5))                                                                         ///
>                         line(data(data/C-USA_CA)) title(F. Droughts, size(*1.4))

. graph export "results/figures/Fig2F_map-droughts.png", as(png) replace
(file results/figures/Fig2F_map-droughts.png written in PNG format)

. graph export "results/figures/Fig2F_map-droughts.pdf", as(pdf) replace
(file results/figures/Fig2F_map-droughts.pdf written in PDF format)

. 
. ***************************************************************************************************
. ****         Fig 3. Identification                                                                                                     ****
. ***************************************************************************************************
. ***************************************************************************************************
. ****             a. Droughts                                                                                   ****
. ***************************************************************************************************
. preserve

.         keep if sample_ols == 1 & iAGRI_PF != . & iSUM3MO_DROUGHT3340!= .
(48 observations deleted)

.         xtile iSUM3MO_DROUGHT3340_50 = iSUM3MO_DROUGHT3340 , n(50)

.         collapse (mean) iAGRI_PF iSUM3MO_DROUGHT3340 , by(iSUM3MO_DROUGHT3340_50)

.         format iAGRI_PF iSUM3MO_DROUGHT3340 %2.1f

.         twoway (scatter iAGRI_PF iSUM3MO_DROUGHT3340 , mfcolor(none) mlcolor(black)) ///
>                    (lfit    iAGRI_PF iSUM3MO_DROUGHT3340 , lcolor(red)                 ), ylabel( , format(%2.1f) angle(0) labsize(large)) leg
> end(off) xlabel(0(1)3, format(%2.0f) grid labsize(large)) xtitle(New Deal drought, size(large)) ytitle(" ") title(A. Agricultural support, siz
> e(huge))  ylabel( , grid labsize(large)) plotregion(fcolor(white)) graphregion(fcolor(white)) scheme(s1manual) name(g1, replace) 

. restore

. 
. preserve

.         keep if sample_ols == 1 & iwarbond_1944_PC != . & iSUM3MO_DROUGHT3340 != . & ww1_vol_sh != . & ww1_awards_pop10_is != .
(48 observations deleted)

.         reg iwarbond_1944_PC ww1_vol_sh ww1_awards_pop10_is 

      Source |       SS           df       MS      Number of obs   =     3,022
-------------+----------------------------------   F(2, 3019)      =    125.80
       Model |  106.254929         2  53.1274646   Prob > F        =    0.0000
    Residual |  1274.99699     3,019  .422324276   R-squared       =    0.0769
-------------+----------------------------------   Adj R-squared   =    0.0763
       Total |  1381.25192     3,021  .457216789   Root MSE        =    .64986

-------------------------------------------------------------------------------------
   iwarbond_1944_PC |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
         ww1_vol_sh |   .5955832   .0469426    12.69   0.000     .5035405    .6876259
ww1_awards_pop10_is |   1.089459   .1291976     8.43   0.000     .8361345    1.342783
              _cons |   4.385218    .021185   207.00   0.000     4.343679    4.426756
-------------------------------------------------------------------------------------

.         predict e, resid

.         xtile iSUM3MO_DROUGHT3340_50 = iSUM3MO_DROUGHT3340 , n(50)

.         collapse (mean) e iSUM3MO_DROUGHT3340 , by(iSUM3MO_DROUGHT3340_50)

.         twoway (scatter e iSUM3MO_DROUGHT3340 , mfcolor(none) mlcolor(black)) ///
>                    (lfit    e iSUM3MO_DROUGHT3340 , lcolor(red)                 ), ylabel( , format(%2.1f) labsize(large) angle(0) grid) legen
> d(off) xlabel(0(1)3, grid labsize(large)) xtitle(New Deal drought, size(large)) ytitle(, size(large)) title(B. War bonds, size(huge))  name(g2
> , replace) plotregion(fcolor(white)) graphregion(fcolor(white)) scheme(s1manual)

. restore

. 
. preserve

.         keep if sample_ols == 1 & ww2_vol_pop40 != . & iSUM3MO_DROUGHT3340 != . & servicecommand != 7 & ww1_vol_sh != . & ww1_awards_pop10_is 
> != .
(741 observations deleted)

.         reg ww2_vol_pop40 ww1_vol_sh ww1_awards_pop10_is 

      Source |       SS           df       MS      Number of obs   =     2,329
-------------+----------------------------------   F(2, 2326)      =     39.11
       Model |  8.84626729         2  4.42313364   Prob > F        =    0.0000
    Residual |  263.091202     2,326  .113108857   R-squared       =    0.0325
-------------+----------------------------------   Adj R-squared   =    0.0317
       Total |  271.937469     2,328  .116811628   Root MSE        =    .33632

-------------------------------------------------------------------------------------
      ww2_vol_pop40 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
         ww1_vol_sh |   .1846437   .0287572     6.42   0.000     .1282513    .2410361
ww1_awards_pop10_is |   .4146666    .075391     5.50   0.000     .2668262    .5625071
              _cons |   .5477097   .0124206    44.10   0.000     .5233532    .5720662
-------------------------------------------------------------------------------------

.         predict e, resid

.         xtile iSUM3MO_DROUGHT3340_50 = iSUM3MO_DROUGHT3340 , n(50)

.         collapse (mean) e iSUM3MO_DROUGHT3340 , by(iSUM3MO_DROUGHT3340_50)

.         twoway (scatter e iSUM3MO_DROUGHT3340 , mfcolor(none) mlcolor(black)) ///
>                    (lfit    e iSUM3MO_DROUGHT3340 , lcolor(red)                 ), ylabel( , format(%2.1f) labsize(large) angle(0) grid) legen
> d(off) xlabel(0(1)3, grid labsize(large)) xtitle(New Deal drought, size(large)) ytitle(, size(large)) title(C. Volunteers, size(huge)) name(g3
> , replace) plotregion(fcolor(white)) graphregion(fcolor(white)) scheme(s1manual) 

. restore

. 
. 
. preserve

.         keep if sample_ols == 1 & ww2_awards_pop40_is != . & iSUM3MO_DROUGHT3340 != . & servicecommand != 7 & ww1_vol_sh != . & ww1_awards_pop
> 10_is != .
(741 observations deleted)

.         reg ww2_awards_pop40_is ww1_vol_sh ww1_awards_pop10_is 

      Source |       SS           df       MS      Number of obs   =     2,329
-------------+----------------------------------   F(2, 2326)      =     43.77
       Model |  1.37556405         2  .687782025   Prob > F        =    0.0000
    Residual |  36.5511911     2,326  .015714184   R-squared       =    0.0363
-------------+----------------------------------   Adj R-squared   =    0.0354
       Total |  37.9267552     2,328  .016291562   Root MSE        =    .12536

-------------------------------------------------------------------------------------
ww2_awards_pop40_is |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
         ww1_vol_sh |   .0761879   .0107187     7.11   0.000     .0551686    .0972071
ww1_awards_pop10_is |   .1529512   .0281007     5.44   0.000     .0978462    .2080562
              _cons |   .1057512   .0046296    22.84   0.000     .0966727    .1148297
-------------------------------------------------------------------------------------

.         predict e, resid

.         xtile iSUM3MO_DROUGHT3340_50 = iSUM3MO_DROUGHT3340 , n(50)

.         collapse (mean) e iSUM3MO_DROUGHT3340 , by(iSUM3MO_DROUGHT3340_50)

.         twoway (scatter e iSUM3MO_DROUGHT3340 , mfcolor(none) mlcolor(black)) ///
>                    (lfit    e iSUM3MO_DROUGHT3340 , lcolor(red)                 ), ylabel( , format(%3.2f) labsize(large) angle(0) grid) legen
> d(off) xlabel(0(1)3, grid labsize(large)) xtitle(New Deal drought, size(large)) ytitle(, size(large)) title(D. Medals, size(huge))  name(g4, r
> eplace) plotregion(fcolor(white)) graphregion(fcolor(white)) scheme(s1manual) 

. restore

. graph combine g1 g2 g3 g4, r(2) plotregion(fcolor(white)) graphregion(fcolor(white)) scheme(s1manual) 

. graph export "results/figures/Fig3A-D_id-droughts.png", as(png) replace
(file results/figures/Fig3A-D_id-droughts.png written in PNG format)

. graph export "results/figures/Fig3A-D_id-droughts.pdf", as(pdf) replace
(file results/figures/Fig3A-D_id-droughts.pdf written in PDF format)

. graph drop    g1 g2 g3 g4

. 
. ***************************************************************************************************
. ****             b. Committees                                                                             ****
. ***************************************************************************************************
. preserve

.         keep if sample_ols == 1 & iAGRI_PF != . & iAGRI_T73 != . 
(48 observations deleted)

.         areg iAGRI_T73 , absorb(stateicpsr)

Linear regression, absorbing indicators         Number of obs     =      3,022
Absorbed variable: stateicpsr                   No. of categories =         48
                                                F(   0,   2974)   =          .
                                                Prob > F          =          .
                                                R-squared         =     0.1745
                                                Adj R-squared     =     0.1615
                                                Root MSE          =     0.4213

------------------------------------------------------------------------------
   iAGRI_T73 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       _cons |   .1298102   .0076631    16.94   0.000     .1147847    .1448357
------------------------------------------------------------------------------
F test of absorbed indicators: F(47, 2974) = 13.376           Prob > F = 0.000

.         predict x, resid

.         areg iAGRI_PF , absorb(stateicpsr)

Linear regression, absorbing indicators         Number of obs     =      3,022
Absorbed variable: stateicpsr                   No. of categories =         48
                                                F(   0,   2974)   =          .
                                                Prob > F          =          .
                                                R-squared         =     0.4975
                                                Adj R-squared     =     0.4896
                                                Root MSE          =     0.7559

------------------------------------------------------------------------------
    iAGRI_PF |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       _cons |   6.634541   .0137506   482.49   0.000     6.607579    6.661502
------------------------------------------------------------------------------
F test of absorbed indicators: F(47, 2974) = 62.658           Prob > F = 0.000

.         predict y, resid

.         
.         xtile x_50 = x , n(50)

.         collapse (mean) y x , by(x_50)

.         format y x %2.1f

.         twoway (scatter y x , mfcolor(none) mlcolor(black)) ///
>                    (lfit    y x , lcolor(red)                 ), ylabel( , grid format(%2.1f) angle(0) labsize(large)) legend(off) xlabel( , f
> ormat(%2.1f)  grid labsize(large)) xtitle(Tenure agri committee, size(large)) ytitle(" ") title(E. Agricultural support, size(huge))  ylabel( 
> , grid labsize(large)) plotregion(fcolor(white)) graphregion(fcolor(white)) scheme(s1manual) name(g1, replace) 

. restore

. 
. preserve

.         keep if sample_ols == 1 & iwarbond_1944_PC != . & iAGRI_T73 != . & ww1_vol_sh != . & ww1_awards_pop10_is != .
(48 observations deleted)

.         areg iAGRI_T73 , absorb(stateicpsr)

Linear regression, absorbing indicators         Number of obs     =      3,022
Absorbed variable: stateicpsr                   No. of categories =         48
                                                F(   0,   2974)   =          .
                                                Prob > F          =          .
                                                R-squared         =     0.1745
                                                Adj R-squared     =     0.1615
                                                Root MSE          =     0.4213

------------------------------------------------------------------------------
   iAGRI_T73 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       _cons |   .1298102   .0076631    16.94   0.000     .1147847    .1448357
------------------------------------------------------------------------------
F test of absorbed indicators: F(47, 2974) = 13.376           Prob > F = 0.000

.         predict x, resid

.         areg iwarbond_1944_PC ww1_vol_sh ww1_awards_pop10_is  , absorb(stateicpsr)

Linear regression, absorbing indicators         Number of obs     =      3,022
Absorbed variable: stateicpsr                   No. of categories =         48
                                                F(   2,   2972)   =      63.32
                                                Prob > F          =     0.0000
                                                R-squared         =     0.4489
                                                Adj R-squared     =     0.4398
                                                Root MSE          =     0.5061

-------------------------------------------------------------------------------------
   iwarbond_1944_PC |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
         ww1_vol_sh |   .3668103   .0410043     8.95   0.000     .2864107    .4472099
ww1_awards_pop10_is |   .6341578   .1051121     6.03   0.000      .428058    .8402577
              _cons |   4.491964   .0177676   252.82   0.000     4.457126    4.526802
-------------------------------------------------------------------------------------
F test of absorbed indicators: F(47, 2972) = 42.682           Prob > F = 0.000

.         predict y, resid

.         
.         xtile x_50 = x , n(50)

.         collapse (mean) y x , by(x_50)

.         format y x %2.1f

.         twoway (scatter y x , mfcolor(none) mlcolor(black)) ///
>                    (lfit    y x , lcolor(red)                 ) , ylabel( , format(%2.1f) labsize(large) angle(0) grid) legend(off) xlabel(, g
> rid labsize(large)) xtitle(Tenure agri committee, size(large)) ytitle(, size(large)) title(F. War bonds, size(huge))  name(g2, replace) plotre
> gion(fcolor(white)) graphregion(fcolor(white)) scheme(s1manual)

. restore

. 
. preserve

.         keep if sample_ols == 1 & ww2_vol_pop40 != . & iAGRI_T73 != . & servicecommand != 7 & ww1_vol_sh != . & ww1_awards_pop10_is != .
(741 observations deleted)

.         areg iAGRI_T73 , absorb(stateicpsr)

Linear regression, absorbing indicators         Number of obs     =      2,329
Absorbed variable: stateicpsr                   No. of categories =         39
                                                F(   0,   2290)   =          .
                                                Prob > F          =          .
                                                R-squared         =     0.1521
                                                Adj R-squared     =     0.1380
                                                Root MSE          =     0.4145

------------------------------------------------------------------------------
   iAGRI_T73 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       _cons |   .1196237   .0085891    13.93   0.000     .1027806    .1364668
------------------------------------------------------------------------------
F test of absorbed indicators: F(38, 2290) = 10.811           Prob > F = 0.000

.         predict x, resid

.         areg ww2_vol_pop40 ww1_vol_sh ww1_awards_pop10_is , absorb(stateicpsr)

Linear regression, absorbing indicators         Number of obs     =      2,329
Absorbed variable: stateicpsr                   No. of categories =         39
                                                F(   2,   2288)   =      70.60
                                                Prob > F          =     0.0000
                                                R-squared         =     0.5209
                                                Adj R-squared     =     0.5125
                                                Root MSE          =     0.2386

-------------------------------------------------------------------------------------
      ww2_vol_pop40 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
         ww1_vol_sh |   .2333435   .0229467    10.17   0.000     .1883451     .278342
ww1_awards_pop10_is |   .2858333   .0565027     5.06   0.000     .1750315    .3966351
              _cons |   .5386931   .0094749    56.85   0.000     .5201128    .5572735
-------------------------------------------------------------------------------------
F test of absorbed indicators: F(38, 2288) = 61.374           Prob > F = 0.000

.         predict y, resid

.         
.         xtile x_50 = x , n(50)

.         collapse (mean) y x , by(x_50)

.         format y x %2.1f

.         twoway (scatter y x , mfcolor(none) mlcolor(black)) ///
>                    (lfit    y x , lcolor(red)                 ) , ylabel( , format(%2.1f) labsize(large) angle(0) grid) legend(off) xlabel(, g
> rid labsize(large)) xtitle(Tenure agri committee, size(large)) ytitle(, size(large)) title(G. Volunteers, size(huge)) name(g3, replace) plotre
> gion(fcolor(white)) graphregion(fcolor(white)) scheme(s1manual) 

. restore

. 
. 
. preserve

.         keep if sample_ols == 1 & ww2_awards_pop40_is != . & iAGRI_T73 != . & servicecommand != 7 & ww1_vol_sh != . & ww1_awards_pop10_is != .
(741 observations deleted)

.         areg iAGRI_T73 , absorb(stateicpsr)

Linear regression, absorbing indicators         Number of obs     =      2,329
Absorbed variable: stateicpsr                   No. of categories =         39
                                                F(   0,   2290)   =          .
                                                Prob > F          =          .
                                                R-squared         =     0.1521
                                                Adj R-squared     =     0.1380
                                                Root MSE          =     0.4145

------------------------------------------------------------------------------
   iAGRI_T73 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       _cons |   .1196237   .0085891    13.93   0.000     .1027806    .1364668
------------------------------------------------------------------------------
F test of absorbed indicators: F(38, 2290) = 10.811           Prob > F = 0.000

.         predict x, resid

.         areg ww2_awards_pop40_is ww1_vol_sh ww1_awards_pop10_is , absorb(stateicpsr)

Linear regression, absorbing indicators         Number of obs     =      2,329
Absorbed variable: stateicpsr                   No. of categories =         39
                                                F(   2,   2288)   =      27.56
                                                Prob > F          =     0.0000
                                                R-squared         =     0.1545
                                                Adj R-squared     =     0.1397
                                                Root MSE          =     0.1184

-------------------------------------------------------------------------------------
ww2_awards_pop40_is |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
         ww1_vol_sh |   .0770715   .0113843     6.77   0.000      .054747    .0993961
ww1_awards_pop10_is |   .0652794    .028032     2.33   0.020     .0103086    .1202502
              _cons |   .1105013   .0047007    23.51   0.000     .1012833    .1197194
-------------------------------------------------------------------------------------
F test of absorbed indicators: F(38, 2288) = 8.418            Prob > F = 0.000

.         predict y, resid

.         
.         xtile x_50 = x , n(50)

.         collapse (mean) y x , by(x_50)

.         format y x %2.1f

.         twoway (scatter y x , mfcolor(none) mlcolor(black)) ///
>                    (lfit    y x , lcolor(red)                 ) , ylabel( , format(%3.2f) labsize(large) angle(0) grid) legend(off) xlabel(, g
> rid labsize(large)) xtitle(Tenure agri committee, size(large)) ytitle(, size(large)) title(H. Medals, size(huge))  name(g4, replace) plotregio
> n(fcolor(white)) graphregion(fcolor(white)) scheme(s1manual) 

. restore

. graph combine g1 g2 g3 g4, r(2) plotregion(fcolor(white)) graphregion(fcolor(white)) scheme(s1manual) 

. graph drop    g1 g2 g3 g4

. graph export "results/figures/Fig3E-H_id-committee.png", as(png) replace
(file results/figures/Fig3E-H_id-committee.png written in PNG format)

. graph export "results/figures/Fig3E-H_id-committee.pdf", as(pdf) replace
(file results/figures/Fig3E-H_id-committee.pdf written in PDF format)

. 
. ***************************************************************************************************
. ****         Fig 4. Pre-New Deal Droughts                                                                                              ****
. ***************************************************************************************************
. ***************************************************************************************************
. ****                 a. Droughts and AAA spending overtime                                                 ****
. ***************************************************************************************************
. 
. preserve

.         use C:/X/patriot, replace

.         keep if sample_ols == 1
(48 observations deleted)

.         keeporder stateicpsr countynd SUM3MO_DROUGHT1897 SUM3MO_DROUGHT1898 SUM3MO_DROUGHT1899 SUM3MO_DROUGHT1900 SUM3MO_DROUGHT1901 SUM3MO_DR
> OUGHT1902 SUM3MO_DROUGHT1903 SUM3MO_DROUGHT1904 SUM3MO_DROUGHT1905 SUM3MO_DROUGHT1906 SUM3MO_DROUGHT1907 SUM3MO_DROUGHT1908 SUM3MO_DROUGHT1909
>  SUM3MO_DROUGHT1910 SUM3MO_DROUGHT1911 SUM3MO_DROUGHT1912 SUM3MO_DROUGHT1913 SUM3MO_DROUGHT1914 SUM3MO_DROUGHT1915 SUM3MO_DROUGHT1916 SUM3MO_D
> ROUGHT1917 SUM3MO_DROUGHT1918 SUM3MO_DROUGHT1919 SUM3MO_DROUGHT1920 SUM3MO_DROUGHT1921 SUM3MO_DROUGHT1922 SUM3MO_DROUGHT1923 SUM3MO_DROUGHT192
> 4 SUM3MO_DROUGHT1925 SUM3MO_DROUGHT1926 SUM3MO_DROUGHT1927 SUM3MO_DROUGHT1928 SUM3MO_DROUGHT1929 SUM3MO_DROUGHT1930 SUM3MO_DROUGHT1931 SUM3MO_
> DROUGHT1932 SUM3MO_DROUGHT1933 SUM3MO_DROUGHT1934 SUM3MO_DROUGHT1935 SUM3MO_DROUGHT1936 SUM3MO_DROUGHT1937 SUM3MO_DROUGHT1938 SUM3MO_DROUGHT19
> 39 SUM3MO_DROUGHT1940 

.         reshape long SUM3MO_DROUGHT, i(stateicpsr countynd) j(Year) string
(note: j = 1897 1898 1899 1900 1901 1902 1903 1904 1905 1906 1907 1908 1909 1910 1911 1912 1913 1914 1915 1916 1917 1918 1919 1920 1921 1922 192
> 3 1924 1925 1926 1927 1928 1929 1930 1931 1932 1933 1934 1935 1936 1937 1938 1939 1940)

Data                               wide   ->   long
-----------------------------------------------------------------------------
Number of obs.                     3022   ->  132968
Number of variables                  46   ->       4
j variable (44 values)                    ->   Year
xij variables:
SUM3MO_DROUGHT1897 SUM3MO_DROUGHT1898 ... SUM3MO_DROUGHT1940->SUM3MO_DROUGHT
-----------------------------------------------------------------------------

.         
.         destring Year, replace
Year: all characters numeric; replaced as int

.         
.         collapse (mean) SUM3MO_DROUGHT, by(Year)

.         gen newdeal     =  1.3 if Year == 1936
(43 missing values generated)

.         gen newdeal_lab = "New Deal"

. 
.         format SUM3MO_DROUGHT %2.0f

.         
.         twoway (scatter SUM3MO_DROUGHT Year, mc(black) mfc(none) msize(medsmall))                         ///
>                    (scatter newdeal        Year, mlabel(newdeal_lab) mlabcolor(blue) mlabsize(medsmall) m(i)) /// 
>                    (line    SUM3MO_DROUGHT Year, lc(black)),                                                 ///
>                    xlab(1897 "1897" 1901 "1901" 1905 "1905" 1909 "1909" 1913 "1913" 1917 "1917" 1921 "1921" 1925 "1925" 1929 "1929" 1933 "1933
> " 1937 "1937" 1941 "1941", angle(45) labsize(large)) xtitle("") xline(1932.5, lcolor(blue) lp(dash)) ///
>                  ylab(, format(%2.1f) angle(0) labsize(large)) ytitle("") title(A. Summer months with drought, size(huge)) plotregion(color(wh
> ite)) graphregion(color(white)) legend(off) name(g2, replace) 

.         graph export "results/figures/Fig4A_pre-droughts-byyear.png", replace as(png)
(file results/figures/Fig4A_pre-droughts-byyear.png written in PNG format)

.         graph export "results/figures/Fig4A_pre-droughts-byyear.pdf", replace as(pdf)
(file results/figures/Fig4A_pre-droughts-byyear.pdf written in PDF format)

. restore

. 
. 
. preserve

.         use rawdata/Libecap/Libecap, clear

. 
.         gen newdeal     =  0.025 if Year == 1933
(39 missing values generated)

.         gen newdeal_lab = "New Deal"

.         
.         twoway (scatter Share   Year, mc(black) mfc(none) msize(medsmall))                         ///
>                    (scatter newdeal Year, mlabel(newdeal_lab) mlabcolor(blue) mlabsize(medsmall) m(i)) /// 
>                    (line    Share   Year, lc(black)), xlab(1901 "1901" 1905 "1905" 1909 "1909" 1913 "1913" 1917 "1917" 1921 "1921" 1925 "1925"
>  1929 "1929" 1933 "1933" 1937 "1937" 1941 "1941", angle(45)  labsize(normalsize)) ylab(0 "0%" 0.1 "10%" 0.2 "20%", angle(0) labsize(large)) xt
> itle(" ") ytitle(" ") xline(1932.5, lcolor(blue) lp(dash)) title(B. Public spending: share agriculture, size(huge)) plotregion(color(white)) g
> raphregion(color(white)) legend(off) name(g1, replace) 
(note:  named style normalsize not found in class gsize, default attributes used)

.         graph export "results/figures/Fig4B_pre-aaa-Libecap.png", replace as(png)
(file results/figures/Fig4B_pre-aaa-Libecap.png written in PNG format)

.         graph export "results/figures/Fig4B_pre-aaa-Libecap.pdf", replace as(pdf)
(file results/figures/Fig4B_pre-aaa-Libecap.pdf written in PDF format)

. restore

. 
. ***************************************************************************************************
. ****                b. Patriotism and pre-New Deal droughts                                                ****
. ***************************************************************************************************
. 
. tab stateicpsr, gen(state)

 State code |
    (ICPSR) |      Freq.     Percent        Cum.
------------+-----------------------------------
          1 |          8        0.26        0.26
          2 |         16        0.52        0.78
          3 |         14        0.46        1.24
          4 |         10        0.33        1.56
          5 |          5        0.16        1.73
          6 |         14        0.46        2.18
         11 |          3        0.10        2.28
         12 |         21        0.68        2.96
         13 |         58        1.89        4.85
         14 |         67        2.18        7.04
         21 |        102        3.32       10.36
         22 |         92        3.00       13.36
         23 |         83        2.70       16.06
         24 |         88        2.87       18.93
         25 |         71        2.31       21.24
         31 |         99        3.22       24.46
         32 |        105        3.42       27.88
         33 |         87        2.83       30.72
         34 |        114        3.71       34.43
         35 |         93        3.03       37.46
         36 |         53        1.73       39.19
         37 |         69        2.25       41.43
         40 |        100        3.26       44.69
         41 |         67        2.18       46.87
         42 |         75        2.44       49.32
         43 |         67        2.18       51.50
         44 |        159        5.18       56.68
         45 |         64        2.08       58.76
         46 |         82        2.67       61.43
         47 |        100        3.26       64.69
         48 |         46        1.50       66.19
         49 |        254        8.27       74.46
         51 |        120        3.91       78.37
         52 |         24        0.78       79.15
         53 |         77        2.51       81.66
         54 |         95        3.09       84.76
         56 |         55        1.79       86.55
         61 |         14        0.46       87.00
         62 |         63        2.05       89.06
         63 |         44        1.43       90.49
         64 |         57        1.86       92.35
         65 |         17        0.55       92.90
         66 |         31        1.01       93.91
         67 |         29        0.94       94.85
         68 |         24        0.78       95.64
         71 |         58        1.89       97.52
         72 |         36        1.17       98.70
         73 |         39        1.27       99.97
         98 |          1        0.03      100.00
------------+-----------------------------------
      Total |      3,070      100.00

. 
. local dependents iAGRI_PF_Z iwarbond_1944_PC_Z ww2_vol_pop40_Z ww1_vol_pop10_Z ww2_awards_pop40_is_Z ww1_awards_pop10_is_Z

. graph close _all    

. foreach dependent of local dependents {
  2.         local drought_title "Summer months of droughts (i.h.s.)"
  3.         local drought_name  "logsum3"
  4.         local drought_pre   "iSUM3MO_DROUGHT"
  5.         
.         if "`dependent'" == "iAGRI_PF_Z"                local           title "C. Agricultural support"
  6.         if "`dependent'" == "iwarbond_1944_PC_Z"    local           title "D. War bonds"
  7.         if "`dependent'" == "ww2_vol_pop40_Z"       local           title "E. Volunteers (WWII)"
  8.         if "`dependent'" == "ww2_awards_pop40_is_Z" local           title "F. Medals (WWII)"
  9.         if "`dependent'" == "ww1_vol_pop10_Z"       local           title "G. Volunteers (WWI)"
 10.         if "`dependent'" == "ww1_awards_pop10_is_Z" local           title "H. Medals (WWI)"
 11. 
.         if "`dependent'" == "iAGRI_PF_Z"                local dependent_title "AAA"
 12.         if "`dependent'" == "iwarbond_1944_PC_Z"    local dependent_title "bond"
 13.         if "`dependent'" == "ww1_vol_pop10_Z"       local dependent_title "volunteer_wwi"
 14.         if "`dependent'" == "ww2_vol_pop40_Z"       local dependent_title "volunteer_wwii"
 15.         if "`dependent'" == "ww1_awards_pop10_is_Z" local dependent_title "medal_wwi"
 16.         if "`dependent'" == "ww2_awards_pop40_is_Z" local dependent_title "medal_wwii"
 17.         
.         if "`dependent'" == "iAGRI_PF_Z"                local if                                
 18.         if "`dependent'" == "iwarbond_1944_PC_Z"    local if
 19.         if "`dependent'" == "ww1_vol_pop10_Z"       local if                            
 20.         if "`dependent'" == "ww2_vol_pop40_Z"       local if                            "& servicecommand != 7"
 21.         if "`dependent'" == "ww1_awards_pop10_is_Z" local if                            
 22.         if "`dependent'" == "ww2_awards_pop40_is_Z" local if                            "& servicecommand != 7"
 23.         
.         if "`dependent'" == "iAGRI_PF_Z"                local droughtlist       "iSUM3MO_DROUGHT9700_Z iSUM3MO_DROUGHT0104_Z iSUM3MO_DROUGHT05
> 08_Z iSUM3MO_DROUGHT0912_Z iSUM3MO_DROUGHT1316_Z iSUM3MO_DROUGHT1720_Z iSUM3MO_DROUGHT2124_Z iSUM3MO_DROUGHT2528_Z iSUM3MO_DROUGHT2932_Z iSUM3
> MO_DROUGHT3340_Z"                   
 24.         if "`dependent'" == "iwarbond_1944_PC_Z"    local droughtlist   "iSUM3MO_DROUGHT9700_Z iSUM3MO_DROUGHT0104_Z iSUM3MO_DROUGHT0508_Z 
> iSUM3MO_DROUGHT0912_Z iSUM3MO_DROUGHT1316_Z iSUM3MO_DROUGHT1720_Z iSUM3MO_DROUGHT2124_Z iSUM3MO_DROUGHT2528_Z iSUM3MO_DROUGHT2932_Z iSUM3MO_DR
> OUGHT3340_Z"
 25.         if "`dependent'" == "ww1_vol_pop10_Z"       local droughtlist   "iSUM3MO_DROUGHT9700_Z iSUM3MO_DROUGHT0104_Z iSUM3MO_DROUGHT0508_Z 
> iSUM3MO_DROUGHT0912_Z iSUM3MO_DROUGHT1316_Z"                                         
 26.         if "`dependent'" == "ww2_vol_pop40_Z"       local droughtlist   "iSUM3MO_DROUGHT9700_Z iSUM3MO_DROUGHT0104_Z iSUM3MO_DROUGHT0508_Z 
> iSUM3MO_DROUGHT0912_Z iSUM3MO_DROUGHT1316_Z iSUM3MO_DROUGHT1720_Z iSUM3MO_DROUGHT2124_Z iSUM3MO_DROUGHT2528_Z iSUM3MO_DROUGHT2932_Z iSUM3MO_DR
> OUGHT3340_Z"
 27.         if "`dependent'" == "ww1_awards_pop10_is_Z" local droughtlist   "iSUM3MO_DROUGHT9700_Z iSUM3MO_DROUGHT0104_Z iSUM3MO_DROUGHT0508_Z 
> iSUM3MO_DROUGHT0912_Z iSUM3MO_DROUGHT1316_Z"                                         
 28.         if "`dependent'" == "ww2_awards_pop40_is_Z" local droughtlist   "iSUM3MO_DROUGHT9700_Z iSUM3MO_DROUGHT0104_Z iSUM3MO_DROUGHT0508_Z 
> iSUM3MO_DROUGHT0912_Z iSUM3MO_DROUGHT1316_Z iSUM3MO_DROUGHT1720_Z iSUM3MO_DROUGHT2124_Z iSUM3MO_DROUGHT2528_Z iSUM3MO_DROUGHT2932_Z iSUM3MO_DR
> OUGHT3340_Z"
 29.         
.         if "`dependent'" == "iAGRI_PF_Z"                local yy                        "9700 0104 0508 0912 1316 1720 2124 2528 2932 3340"   
>                   
 30.         if "`dependent'" == "iwarbond_1944_PC_Z"    local yy                    "9700 0104 0508 0912 1316 1720 2124 2528 2932 3340"
 31.         if "`dependent'" == "ww1_vol_pop10_Z"       local yy                    "9700 0104 0508 0912 1316"                      
 32.         if "`dependent'" == "ww2_vol_pop40_Z"       local yy                    "9700 0104 0508 0912 1316 1720 2124 2528 2932 3340"
 33.         if "`dependent'" == "ww1_awards_pop10_is_Z" local yy                    "9700 0104 0508 0912 1316"                                 
>      
 34.         if "`dependent'" == "ww2_awards_pop40_is_Z" local yy                    "9700 0104 0508 0912 1316 1720 2124 2528 2932 3340"     
 35. 
.         if "`dependent'" == "iAGRI_PF_Z"                macro def control       "ww1_vol_sh_Z ww1_awards_pop10_is_Z lpop30_Z c30unemp_Z c30urb
> an1_Z c30farm_Z Yf_T29_Z MEAN9628_Z c30men_Z c30black_Z c30jap_Z c30deu_Z c30ita_Z c30vet_Z lc40wage_Z iwarconpro_PC_Z "                  
 36.         if "`dependent'" == "iwarbond_1944_PC_Z"    macro def control   "ww1_vol_sh_Z ww1_awards_pop10_is_Z lpop30_Z c30unemp_Z c30urban1_Z
>  c30farm_Z Yf_T29_Z MEAN9628_Z c30men_Z c30black_Z c30jap_Z c30deu_Z c30ita_Z c30vet_Z lc40wage_Z iwarconpro_PC_Z "
 37.         if "`dependent'" == "ww1_vol_pop10_Z"       macro def control   "lpop10_Z c10unemp_Z c10urban1_Z c10men_Z c10black_Z c10jap_Z c10de
> u_Z c10ita_Z "                       
 38.         if "`dependent'" == "ww2_vol_pop40_Z"           macro def control       "ww1_vol_sh_Z ww1_awards_pop10_is_Z lpop30_Z c30unemp_Z c30
> urban1_Z c30farm_Z Yf_T29_Z MEAN9628_Z c30men_Z c30black_Z c30jap_Z c30deu_Z c30ita_Z c30vet_Z lc40wage_Z iwarconpro_PC_Z "
 39.         if "`dependent'" == "ww1_awards_pop10_is_Z" macro def control   "lpop10_Z c10unemp_Z c10urban1_Z c10men_Z c10black_Z c10jap_Z c10de
> u_Z c10ita_Z "                       
 40.         if "`dependent'" == "ww2_awards_pop40_is_Z" macro def control   "ww1_vol_sh_Z ww1_awards_pop10_is_Z lpop30_Z c30unemp_Z c30urban1_Z
>  c30farm_Z Yf_T29_Z MEAN9628_Z c30men_Z c30black_Z c30jap_Z c30deu_Z c30ita_Z c30vet_Z lc40wage_Z iwarconpro_PC_Z"
 41.         
.         foreach spec in "$control"{
 42.                 if "`spec'" == "$control"                                local spec_name       "(state FEs)"
 43.                 if "`spec'" == "$control"                                local spec_title      "statefe"
 44.                 
.                 cap drop *_Z
 45.                 foreach d in iAGRI_PF iwarbond_1944_PC ww2_vol_pop40 ww1_vol_sh ww1_vol_pop10 ww2_awards_pop40_is ww1_awards_pop10_is{
 46.                         egen `d'_Z = std(`d') if sample_ols == 1 `if'
 47.                 }
 48. 
.                 foreach d of var state1-state49{
 49.                         egen `d'_Z = std(`d') if sample_ols == 1 `if'
 50.                 }
 51. 
.                 foreach d in lpop30 c30unemp c30urban1 c30farm Yf_T29 MEAN9628 c30men c30black c30jap c30deu c30ita c30vet lc40wage iwarconpro
> _PC{
 52.                         egen `d'_Z = std(`d') if sample_ols == 1 `if'
 53.                 }
 54. 
.                 foreach d in lpop10 c10unemp c10urban1 c10men c10black c10jap c10deu c10ita{
 55.                         egen `d'_Z = std(`d') if sample_ols == 1 `if'
 56.                 }
 57. 
.                 foreach d in iSUM3MO_DROUGHT9700 iSUM3MO_DROUGHT0104 iSUM3MO_DROUGHT0508 iSUM3MO_DROUGHT0912 iSUM3MO_DROUGHT1316 iSUM3MO_DROUG
> HT1720 iSUM3MO_DROUGHT2124 iSUM3MO_DROUGHT2528 iSUM3MO_DROUGHT2932 iSUM3MO_DROUGHT3340{
 58.                         egen `d'_Z = std(`d') if sample_ols == 1 `if'   
 59.                 }
 60. 
. drop state49_Z
 61. 
. if "`if'" == "& servicecommand != 7"{
 62.         drop state16_Z state17_Z state18_Z state19_Z state20_Z state21_Z state22_Z state39_Z state45_Z
 63. }       
 64. estimates clear
 65. 
. xi: reg `dependent' `droughtlist' `spec'  state*_Z if sample_ols == 1  `if', cluster(CLIMDIVX)
 66. 
.          foreach year in `yy'{
 67.                 local b_`dependent'_`year' = _b[`drought_pre'`year']
 68.                 local s_`dependent'_`year' = _se[`drought_pre'`year']
 69.                 } /* forvalues year */
 70.                 
. preserve 
 71. 
.                 clear
 72.                 set obs 20
 73.                 gen years = .
 74.                 gen b    = .
 75.                 gen s    = .
 76.                 gen l    =.
 77.                 gen h    =.
 78.                 gen ord  = ""
 79.                 local j 0
 80. 
.                 foreach year in `yy'{
 81.         
.                         if "`year'" == "9700"    local           years "1897-1900"
 82.                         if "`year'" == "0104"    local           years "1900-1904"
 83.                         if "`year'" == "0508"    local           years "1905-1908"
 84.                         if "`year'" == "0912"    local                   years "1909-1912"
 85.                         if "`year'" == "1316"    local                   years "1913-1916"
 86.                         if "`year'" == "1720"    local           years "1917-1920"
 87.                         if "`year'" == "2124"    local           years "1921-1924"
 88.                         if "`year'" == "2528"    local           years "1925-1928"
 89.                         if "`year'" == "2932"    local                   years "1929-1932"
 90.                         if "`year'" == "3340"    local                   years "1933-1940"
 91. 
.                         local j =               `j' + 1
 92.                         qui replace years = `j'                                           if _n==`j'
 93.                         qui replace ord = "`years'"                               if _n == `j'
 94.                         qui replace b    = `b_`dependent'_`year''     if _n == `j'
 95.                         qui replace s    = `s_`dependent'_`year''     if _n == `j'
 96.                         qui replace l    =   b - 1.96 * s                         if _n == `j'
 97.                         qui replace h    =   b + 1.96 * s                         if _n == `j'
 98.                 } /* forvalues year */ 
 99.                 
.                 
.         labmask years, val(ord)
100.         
.         sort  years
101.         qui separate b, by(years)
102.         qui separate h, by(years)
103.         qui separate l, by(years)
104.         
.         qui sum h
105.         
.         local maxv`dependent' `r(max)'
106.         
.         if "`maxvww1_vol_pop10_Z'" != "" & "`maxvww2_vol_pop40_Z'" != ""{
107.                 local maxvww1_vol_pop10_Z = `maxvww2_vol_pop40_Z'
108.         }
109.         if "`maxvww2_awards_pop40_is_Z'" != "" & "`maxvww1_awards_pop10_is_Z'" != ""{
110.                 local maxvww1_awards_pop10_is_Z = `maxvww2_awards_pop40_is_Z'
111.         }
112.         
.         if "`yy'" == "9700 0104 0508 0912 1316 1720 2124 2528 2932 3340"{
113.                                 twoway (scatter b1      years,  mcolor(red%40)    mfcolor(none) msize(*0.8) msymbol(oh))                   
>              ///
>                            (scatter b2  years,  mcolor(red%40)    mfcolor(none) msize(*0.8) msymbol(oh))                                ///
>                        (scatter b3      years,  mcolor(red%40)    mfcolor(none) msize(*0.8) msymbol(oh))                                ///
>                            (scatter b4  years,  mcolor(red%40)    mfcolor(none) msize(*0.8) msymbol(oh))                                ///
>                            (scatter b5  years,  mcolor(red%40)    mfcolor(none) msize(*0.8) msymbol(oh))                        ///
>                            (scatter b6  years,  mcolor(red%40)    mfcolor(none) msize(*0.8) msymbol(oh))                                ///
>                        (scatter b7      years,  mcolor(red%40)    mfcolor(none) msize(*0.8) msymbol(oh))                                ///
>                            (scatter b8  years,  mcolor(red%40)    mfcolor(none) msize(*0.8) msymbol(oh))                                ///
>                            (scatter b9  years,  mcolor(red%40)    mfcolor(none) msize(*0.8) msymbol(oh))                                ///
>                        (scatter b10     years,  mcolor(red)       mfcolor(none) msize(*0.8) msymbol(oh))                                ///
>                            (rcap h1 l1  years,  blcolor(red%40)   blwidth(medthick) blpattern(solid))                                   ///
>                            (rcap h2 l2  years,  blcolor(red%40)   blwidth(medthick) blpattern(solid))                                   ///   
>              
>                            (rcap h3 l3  years,  blcolor(red%40)   blwidth(medthick) blpattern(solid))                                   ///
>                            (rcap h4 l4  years,  blcolor(red%40)   blwidth(medthick) blpattern(solid))                                   ///
>                            (rcap h5 l5  years,  blcolor(red%40)   blwidth(medthick) blpattern(solid))                                   ///   
>   
>                            (rcap h6 l6  years,  blcolor(red%40)   blwidth(medthick) blpattern(solid))                                   ///
>                            (rcap h7 l7  years,  blcolor(red%40)   blwidth(medthick) blpattern(solid))                                   ///   
>              
>                            (rcap h8 l8  years,  blcolor(red%40)   blwidth(medthick) blpattern(solid))                                   ///
>                            (rcap h9 l9  years,  blcolor(red%40)   blwidth(medthick) blpattern(solid))                                   ///
>                            (rcap h10 l10 years,  blcolor(red)     blwidth(medthick) blpattern(solid)),                                  ///   
>              
>                                 legend(off) yline(0, lcolor(black)) xline(9.5, lcolor(navy) lpattern(dash))                             ///
>                                 yscale(range(-`maxv`dependent'' `maxv`dependent'')) ylabel(-`maxv`dependent'' 0 `maxv`dependent'', angle(0) la
> bsize(*1.4) format(%9.3f)) ytitle( )         ///
>                                 xlabel(1(1)10, valuelabel labsize(*1.1) angle(45)) xtitle("Months of droughts", size(large)) xscale(range(0.5 
> 10.5)) title(`title', size(huge)) ///
>                                 graphregion(fcolor(white)) plotregion(fcolor(white)) scheme(s1manual) name("`dependent_title'_`drought_name'_`
> spec_title'", replace)
114.                 
.                 graph export "results/figures/Fig4C-H_pre-`dependent_title'.png", replace as(png)
115.                 graph export "results/figures/Fig4C-H_pre-`dependent_title'.pdf", replace as(pdf)
116.         restore
117.         }
118.         
.                 if "`yy'" == "9700 0104 0508 0912 1316"{
119.                         twoway (scatter b1      years,  mcolor(red%40)    mfcolor(none) msize(*0.8) msymbol(oh))                           
>      ///
>                                    (scatter b2  years,  mcolor(red%40)    mfcolor(none) msize(*0.8) msymbol(oh))                              
>   ///
>                                    (scatter b3  years,  mcolor(red%40)    mfcolor(none) msize(*0.8) msymbol(oh))                              
>   ///
>                                    (scatter b4  years,  mcolor(red%40)    mfcolor(none) msize(*0.8) msymbol(oh))                              
>   ///
>                                    (scatter b5  years,  mcolor(red%40)    mfcolor(none) msize(*0.8) msymbol(oh))                        ///
>                                    (rcap h1 l1  years,  blcolor(red%40)   blwidth(medthick) blpattern(solid))                                 
>   ///
>                                    (rcap h2 l2  years,  blcolor(red%40)   blwidth(medthick) blpattern(solid))                                 
>   ///                
>                                    (rcap h3 l3  years,  blcolor(red%40)   blwidth(medthick) blpattern(solid))                                 
>   ///
>                                    (rcap h4 l4  years,  blcolor(red%40)   blwidth(medthick) blpattern(solid))                                 
>   ///
>                                    (rcap h5 l5  years,  blcolor(red%40)   blwidth(medthick) blpattern(solid)),                                
>   ///
>                                         legend(off) yline(0, lcolor(black))                                                                   
>                           ///
>                                         yscale(range(-`maxv`dependent'' `maxv`dependent'')) ylabel(-`maxv`dependent'' 0 `maxv`dependent'', ang
> le(0) labsize(*1.4) format(%9.3f)) ytitle( )  ///
>                                         xlabel(1(1)5, valuelabel labsize(*1.1) angle(45)) xtitle("Months of droughts", size(large)) xscale(ran
> ge(0.5 5.5)) title(`title', size(huge)) ///
>                                         graphregion(fcolor(white)) plotregion(fcolor(white)) scheme(s1manual) name("`dependent_title'_`drought
> _name'_`spec_title'", replace)
120.                 
.                         graph export "results/figures/Fig4C-H_pre-`dependent_title'.png", replace as(png)
121.                         graph export "results/figures/Fig4C-H_pre-`dependent_title'.pdf", replace as(pdf)
122.                 restore 
123.                 }
124.         }
125. }
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(3,070 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
Yf_T29 not found
r(111);

end of do-file

r(111);

. do "C:\Users\locasa\AppData\Local\Temp\STD3f70_000000.tmp"

. local dependents iAGRI_PF_Z iwarbond_1944_PC_Z ww2_vol_pop40_Z ww1_vol_pop10_Z ww2_awards_pop40_is_Z ww1_awards_pop10_is_Z

. graph close _all    

. foreach dependent of local dependents {
  2.         local drought_title "Summer months of droughts (i.h.s.)"
  3.         local drought_name  "logsum3"
  4.         local drought_pre   "iSUM3MO_DROUGHT"
  5.         
.         if "`dependent'" == "iAGRI_PF_Z"                local           title "C. Agricultural support"
  6.         if "`dependent'" == "iwarbond_1944_PC_Z"    local           title "D. War bonds"
  7.         if "`dependent'" == "ww2_vol_pop40_Z"       local           title "E. Volunteers (WWII)"
  8.         if "`dependent'" == "ww2_awards_pop40_is_Z" local           title "F. Medals (WWII)"
  9.         if "`dependent'" == "ww1_vol_pop10_Z"       local           title "G. Volunteers (WWI)"
 10.         if "`dependent'" == "ww1_awards_pop10_is_Z" local           title "H. Medals (WWI)"
 11. 
.         if "`dependent'" == "iAGRI_PF_Z"                local dependent_title "AAA"
 12.         if "`dependent'" == "iwarbond_1944_PC_Z"    local dependent_title "bond"
 13.         if "`dependent'" == "ww1_vol_pop10_Z"       local dependent_title "volunteer_wwi"
 14.         if "`dependent'" == "ww2_vol_pop40_Z"       local dependent_title "volunteer_wwii"
 15.         if "`dependent'" == "ww1_awards_pop10_is_Z" local dependent_title "medal_wwi"
 16.         if "`dependent'" == "ww2_awards_pop40_is_Z" local dependent_title "medal_wwii"
 17.         
.         if "`dependent'" == "iAGRI_PF_Z"                local if                                
 18.         if "`dependent'" == "iwarbond_1944_PC_Z"    local if
 19.         if "`dependent'" == "ww1_vol_pop10_Z"       local if                            
 20.         if "`dependent'" == "ww2_vol_pop40_Z"       local if                            "& servicecommand != 7"
 21.         if "`dependent'" == "ww1_awards_pop10_is_Z" local if                            
 22.         if "`dependent'" == "ww2_awards_pop40_is_Z" local if                            "& servicecommand != 7"
 23.         
.         if "`dependent'" == "iAGRI_PF_Z"                local droughtlist       "iSUM3MO_DROUGHT9700_Z iSUM3MO_DROUGHT0104_Z iSUM3MO_DROUGHT05
> 08_Z iSUM3MO_DROUGHT0912_Z iSUM3MO_DROUGHT1316_Z iSUM3MO_DROUGHT1720_Z iSUM3MO_DROUGHT2124_Z iSUM3MO_DROUGHT2528_Z iSUM3MO_DROUGHT2932_Z iSUM3
> MO_DROUGHT3340_Z"                   
 24.         if "`dependent'" == "iwarbond_1944_PC_Z"    local droughtlist   "iSUM3MO_DROUGHT9700_Z iSUM3MO_DROUGHT0104_Z iSUM3MO_DROUGHT0508_Z 
> iSUM3MO_DROUGHT0912_Z iSUM3MO_DROUGHT1316_Z iSUM3MO_DROUGHT1720_Z iSUM3MO_DROUGHT2124_Z iSUM3MO_DROUGHT2528_Z iSUM3MO_DROUGHT2932_Z iSUM3MO_DR
> OUGHT3340_Z"
 25.         if "`dependent'" == "ww1_vol_pop10_Z"       local droughtlist   "iSUM3MO_DROUGHT9700_Z iSUM3MO_DROUGHT0104_Z iSUM3MO_DROUGHT0508_Z 
> iSUM3MO_DROUGHT0912_Z iSUM3MO_DROUGHT1316_Z"                                         
 26.         if "`dependent'" == "ww2_vol_pop40_Z"       local droughtlist   "iSUM3MO_DROUGHT9700_Z iSUM3MO_DROUGHT0104_Z iSUM3MO_DROUGHT0508_Z 
> iSUM3MO_DROUGHT0912_Z iSUM3MO_DROUGHT1316_Z iSUM3MO_DROUGHT1720_Z iSUM3MO_DROUGHT2124_Z iSUM3MO_DROUGHT2528_Z iSUM3MO_DROUGHT2932_Z iSUM3MO_DR
> OUGHT3340_Z"
 27.         if "`dependent'" == "ww1_awards_pop10_is_Z" local droughtlist   "iSUM3MO_DROUGHT9700_Z iSUM3MO_DROUGHT0104_Z iSUM3MO_DROUGHT0508_Z 
> iSUM3MO_DROUGHT0912_Z iSUM3MO_DROUGHT1316_Z"                                         
 28.         if "`dependent'" == "ww2_awards_pop40_is_Z" local droughtlist   "iSUM3MO_DROUGHT9700_Z iSUM3MO_DROUGHT0104_Z iSUM3MO_DROUGHT0508_Z 
> iSUM3MO_DROUGHT0912_Z iSUM3MO_DROUGHT1316_Z iSUM3MO_DROUGHT1720_Z iSUM3MO_DROUGHT2124_Z iSUM3MO_DROUGHT2528_Z iSUM3MO_DROUGHT2932_Z iSUM3MO_DR
> OUGHT3340_Z"
 29.         
.         if "`dependent'" == "iAGRI_PF_Z"                local yy                        "9700 0104 0508 0912 1316 1720 2124 2528 2932 3340"   
>                   
 30.         if "`dependent'" == "iwarbond_1944_PC_Z"    local yy                    "9700 0104 0508 0912 1316 1720 2124 2528 2932 3340"
 31.         if "`dependent'" == "ww1_vol_pop10_Z"       local yy                    "9700 0104 0508 0912 1316"                      
 32.         if "`dependent'" == "ww2_vol_pop40_Z"       local yy                    "9700 0104 0508 0912 1316 1720 2124 2528 2932 3340"
 33.         if "`dependent'" == "ww1_awards_pop10_is_Z" local yy                    "9700 0104 0508 0912 1316"                                 
>      
 34.         if "`dependent'" == "ww2_awards_pop40_is_Z" local yy                    "9700 0104 0508 0912 1316 1720 2124 2528 2932 3340"     
 35. 
.         if "`dependent'" == "iAGRI_PF_Z"                macro def control       "ww1_vol_sh_Z ww1_awards_pop10_is_Z lpop30_Z c30unemp_Z c30urb
> an1_Z c30farm_Z iYf_T29_Z MEAN9628_Z c30men_Z c30black_Z c30jap_Z c30deu_Z c30ita_Z c30vet_Z lc40wage_Z iwarconpro_PC_Z "                 
 36.         if "`dependent'" == "iwarbond_1944_PC_Z"    macro def control   "ww1_vol_sh_Z ww1_awards_pop10_is_Z lpop30_Z c30unemp_Z c30urban1_Z
>  c30farm_Z iYf_T29_Z MEAN9628_Z c30men_Z c30black_Z c30jap_Z c30deu_Z c30ita_Z c30vet_Z lc40wage_Z iwarconpro_PC_Z "
 37.         if "`dependent'" == "ww1_vol_pop10_Z"       macro def control   "lpop10_Z c10unemp_Z c10urban1_Z c10men_Z c10black_Z c10jap_Z c10de
> u_Z c10ita_Z "                       
 38.         if "`dependent'" == "ww2_vol_pop40_Z"           macro def control       "ww1_vol_sh_Z ww1_awards_pop10_is_Z lpop30_Z c30unemp_Z c30
> urban1_Z c30farm_Z iYf_T29_Z MEAN9628_Z c30men_Z c30black_Z c30jap_Z c30deu_Z c30ita_Z c30vet_Z lc40wage_Z iwarconpro_PC_Z "
 39.         if "`dependent'" == "ww1_awards_pop10_is_Z" macro def control   "lpop10_Z c10unemp_Z c10urban1_Z c10men_Z c10black_Z c10jap_Z c10de
> u_Z c10ita_Z "                       
 40.         if "`dependent'" == "ww2_awards_pop40_is_Z" macro def control   "ww1_vol_sh_Z ww1_awards_pop10_is_Z lpop30_Z c30unemp_Z c30urban1_Z
>  c30farm_Z iYf_T29_Z MEAN9628_Z c30men_Z c30black_Z c30jap_Z c30deu_Z c30ita_Z c30vet_Z lc40wage_Z iwarconpro_PC_Z"
 41.         
.         foreach spec in "$control"{
 42.                 if "`spec'" == "$control"                                local spec_name       "(state FEs)"
 43.                 if "`spec'" == "$control"                                local spec_title      "statefe"
 44.                 
.                 cap drop *_Z
 45.                 foreach d in iAGRI_PF iwarbond_1944_PC ww2_vol_pop40 ww1_vol_sh ww1_vol_pop10 ww2_awards_pop40_is ww1_awards_pop10_is{
 46.                         egen `d'_Z = std(`d') if sample_ols == 1 `if'
 47.                 }
 48. 
.                 foreach d of var state1-state49{
 49.                         egen `d'_Z = std(`d') if sample_ols == 1 `if'
 50.                 }
 51. 
.                 foreach d in lpop30 c30unemp c30urban1 c30farm iYf_T29 MEAN9628 c30men c30black c30jap c30deu c30ita c30vet lc40wage iwarconpr
> o_PC{
 52.                         egen `d'_Z = std(`d') if sample_ols == 1 `if'
 53.                 }
 54. 
.                 foreach d in lpop10 c10unemp c10urban1 c10men c10black c10jap c10deu c10ita{
 55.                         egen `d'_Z = std(`d') if sample_ols == 1 `if'
 56.                 }
 57. 
.                 foreach d in iSUM3MO_DROUGHT9700 iSUM3MO_DROUGHT0104 iSUM3MO_DROUGHT0508 iSUM3MO_DROUGHT0912 iSUM3MO_DROUGHT1316 iSUM3MO_DROUG
> HT1720 iSUM3MO_DROUGHT2124 iSUM3MO_DROUGHT2528 iSUM3MO_DROUGHT2932 iSUM3MO_DROUGHT3340{
 58.                         egen `d'_Z = std(`d') if sample_ols == 1 `if'   
 59.                 }
 60. 
. drop state49_Z
 61. 
. if "`if'" == "& servicecommand != 7"{
 62.         drop state16_Z state17_Z state18_Z state19_Z state20_Z state21_Z state22_Z state39_Z state45_Z
 63. }       
 64. estimates clear
 65. 
. xi: reg `dependent' `droughtlist' `spec'  state*_Z if sample_ols == 1  `if', cluster(CLIMDIVX)
 66. 
.          foreach year in `yy'{
 67.                 local b_`dependent'_`year' = _b[`drought_pre'`year']
 68.                 local s_`dependent'_`year' = _se[`drought_pre'`year']
 69.                 } /* forvalues year */
 70.                 
. preserve 
 71. 
.                 clear
 72.                 set obs 20
 73.                 gen years = .
 74.                 gen b    = .
 75.                 gen s    = .
 76.                 gen l    =.
 77.                 gen h    =.
 78.                 gen ord  = ""
 79.                 local j 0
 80. 
.                 foreach year in `yy'{
 81.         
.                         if "`year'" == "9700"    local           years "1897-1900"
 82.                         if "`year'" == "0104"    local           years "1900-1904"
 83.                         if "`year'" == "0508"    local           years "1905-1908"
 84.                         if "`year'" == "0912"    local                   years "1909-1912"
 85.                         if "`year'" == "1316"    local                   years "1913-1916"
 86.                         if "`year'" == "1720"    local           years "1917-1920"
 87.                         if "`year'" == "2124"    local           years "1921-1924"
 88.                         if "`year'" == "2528"    local           years "1925-1928"
 89.                         if "`year'" == "2932"    local                   years "1929-1932"
 90.                         if "`year'" == "3340"    local                   years "1933-1940"
 91. 
.                         local j =               `j' + 1
 92.                         qui replace years = `j'                                           if _n==`j'
 93.                         qui replace ord = "`years'"                               if _n == `j'
 94.                         qui replace b    = `b_`dependent'_`year''     if _n == `j'
 95.                         qui replace s    = `s_`dependent'_`year''     if _n == `j'
 96.                         qui replace l    =   b - 1.96 * s                         if _n == `j'
 97.                         qui replace h    =   b + 1.96 * s                         if _n == `j'
 98.                 } /* forvalues year */ 
 99.                 
.                 
.         labmask years, val(ord)
100.         
.         sort  years
101.         qui separate b, by(years)
102.         qui separate h, by(years)
103.         qui separate l, by(years)
104.         
.         qui sum h
105.         
.         local maxv`dependent' `r(max)'
106.         
.         if "`maxvww1_vol_pop10_Z'" != "" & "`maxvww2_vol_pop40_Z'" != ""{
107.                 local maxvww1_vol_pop10_Z = `maxvww2_vol_pop40_Z'
108.         }
109.         if "`maxvww2_awards_pop40_is_Z'" != "" & "`maxvww1_awards_pop10_is_Z'" != ""{
110.                 local maxvww1_awards_pop10_is_Z = `maxvww2_awards_pop40_is_Z'
111.         }
112.         
.         if "`yy'" == "9700 0104 0508 0912 1316 1720 2124 2528 2932 3340"{
113.                                 twoway (scatter b1      years,  mcolor(red%40)    mfcolor(none) msize(*0.8) msymbol(oh))                   
>              ///
>                            (scatter b2  years,  mcolor(red%40)    mfcolor(none) msize(*0.8) msymbol(oh))                                ///
>                        (scatter b3      years,  mcolor(red%40)    mfcolor(none) msize(*0.8) msymbol(oh))                                ///
>                            (scatter b4  years,  mcolor(red%40)    mfcolor(none) msize(*0.8) msymbol(oh))                                ///
>                            (scatter b5  years,  mcolor(red%40)    mfcolor(none) msize(*0.8) msymbol(oh))                        ///
>                            (scatter b6  years,  mcolor(red%40)    mfcolor(none) msize(*0.8) msymbol(oh))                                ///
>                        (scatter b7      years,  mcolor(red%40)    mfcolor(none) msize(*0.8) msymbol(oh))                                ///
>                            (scatter b8  years,  mcolor(red%40)    mfcolor(none) msize(*0.8) msymbol(oh))                                ///
>                            (scatter b9  years,  mcolor(red%40)    mfcolor(none) msize(*0.8) msymbol(oh))                                ///
>                        (scatter b10     years,  mcolor(red)       mfcolor(none) msize(*0.8) msymbol(oh))                                ///
>                            (rcap h1 l1  years,  blcolor(red%40)   blwidth(medthick) blpattern(solid))                                   ///
>                            (rcap h2 l2  years,  blcolor(red%40)   blwidth(medthick) blpattern(solid))                                   ///   
>              
>                            (rcap h3 l3  years,  blcolor(red%40)   blwidth(medthick) blpattern(solid))                                   ///
>                            (rcap h4 l4  years,  blcolor(red%40)   blwidth(medthick) blpattern(solid))                                   ///
>                            (rcap h5 l5  years,  blcolor(red%40)   blwidth(medthick) blpattern(solid))                                   ///   
>   
>                            (rcap h6 l6  years,  blcolor(red%40)   blwidth(medthick) blpattern(solid))                                   ///
>                            (rcap h7 l7  years,  blcolor(red%40)   blwidth(medthick) blpattern(solid))                                   ///   
>              
>                            (rcap h8 l8  years,  blcolor(red%40)   blwidth(medthick) blpattern(solid))                                   ///
>                            (rcap h9 l9  years,  blcolor(red%40)   blwidth(medthick) blpattern(solid))                                   ///
>                            (rcap h10 l10 years,  blcolor(red)     blwidth(medthick) blpattern(solid)),                                  ///   
>              
>                                 legend(off) yline(0, lcolor(black)) xline(9.5, lcolor(navy) lpattern(dash))                             ///
>                                 yscale(range(-`maxv`dependent'' `maxv`dependent'')) ylabel(-`maxv`dependent'' 0 `maxv`dependent'', angle(0) la
> bsize(*1.4) format(%9.3f)) ytitle( )         ///
>                                 xlabel(1(1)10, valuelabel labsize(*1.1) angle(45)) xtitle("Months of droughts", size(large)) xscale(range(0.5 
> 10.5)) title(`title', size(huge)) ///
>                                 graphregion(fcolor(white)) plotregion(fcolor(white)) scheme(s1manual) name("`dependent_title'_`drought_name'_`
> spec_title'", replace)
114.                 
.                 graph export "results/figures/Fig4C-H_pre-`dependent_title'.png", replace as(png)
115.                 graph export "results/figures/Fig4C-H_pre-`dependent_title'.pdf", replace as(pdf)
116.         restore
117.         }
118.         
.                 if "`yy'" == "9700 0104 0508 0912 1316"{
119.                         twoway (scatter b1      years,  mcolor(red%40)    mfcolor(none) msize(*0.8) msymbol(oh))                           
>      ///
>                                    (scatter b2  years,  mcolor(red%40)    mfcolor(none) msize(*0.8) msymbol(oh))                              
>   ///
>                                    (scatter b3  years,  mcolor(red%40)    mfcolor(none) msize(*0.8) msymbol(oh))                              
>   ///
>                                    (scatter b4  years,  mcolor(red%40)    mfcolor(none) msize(*0.8) msymbol(oh))                              
>   ///
>                                    (scatter b5  years,  mcolor(red%40)    mfcolor(none) msize(*0.8) msymbol(oh))                        ///
>                                    (rcap h1 l1  years,  blcolor(red%40)   blwidth(medthick) blpattern(solid))                                 
>   ///
>                                    (rcap h2 l2  years,  blcolor(red%40)   blwidth(medthick) blpattern(solid))                                 
>   ///                
>                                    (rcap h3 l3  years,  blcolor(red%40)   blwidth(medthick) blpattern(solid))                                 
>   ///
>                                    (rcap h4 l4  years,  blcolor(red%40)   blwidth(medthick) blpattern(solid))                                 
>   ///
>                                    (rcap h5 l5  years,  blcolor(red%40)   blwidth(medthick) blpattern(solid)),                                
>   ///
>                                         legend(off) yline(0, lcolor(black))                                                                   
>                           ///
>                                         yscale(range(-`maxv`dependent'' `maxv`dependent'')) ylabel(-`maxv`dependent'' 0 `maxv`dependent'', ang
> le(0) labsize(*1.4) format(%9.3f)) ytitle( )  ///
>                                         xlabel(1(1)5, valuelabel labsize(*1.1) angle(45)) xtitle("Months of droughts", size(large)) xscale(ran
> ge(0.5 5.5)) title(`title', size(huge)) ///
>                                         graphregion(fcolor(white)) plotregion(fcolor(white)) scheme(s1manual) name("`dependent_title'_`drought
> _name'_`spec_title'", replace)
120.                 
.                         graph export "results/figures/Fig4C-H_pre-`dependent_title'.png", replace as(png)
121.                         graph export "results/figures/Fig4C-H_pre-`dependent_title'.pdf", replace as(pdf)
122.                 restore 
123.                 }
124.         }
125. }
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(3,070 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
note: state32_Z omitted because of collinearity

Linear regression                               Number of obs     =      3,022
                                                F(72, 338)        =          .
                                                Prob > F          =          .
                                                R-squared         =     0.5741
                                                Root MSE          =     .66068

                                      (Std. Err. adjusted for 339 clusters in CLIMDIVX)
---------------------------------------------------------------------------------------
                      |               Robust
           iAGRI_PF_Z |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
iSUM3MO_DROUGHT9700_Z |   .0170364   .0438927     0.39   0.698    -.0693009    .1033737
iSUM3MO_DROUGHT0104_Z |  -.0391392   .0558665    -0.70   0.484     -.149029    .0707506
iSUM3MO_DROUGHT0508_Z |   .0516556   .0424059     1.22   0.224    -.0317571    .1350684
iSUM3MO_DROUGHT0912_Z |   .0041956   .0497606     0.08   0.933    -.0936838     .102075
iSUM3MO_DROUGHT1316_Z |  -.0108983   .0520731    -0.21   0.834    -.1133265      .09153
iSUM3MO_DROUGHT1720_Z |  -.1023817   .0583023    -1.76   0.080    -.2170628    .0122994
iSUM3MO_DROUGHT2124_Z |   .0435188     .03685     1.18   0.238    -.0289655     .116003
iSUM3MO_DROUGHT2528_Z |  -.0830107    .050702    -1.64   0.103    -.1827418    .0167204
iSUM3MO_DROUGHT2932_Z |  -.0175629   .0377295    -0.47   0.642     -.091777    .0566513
iSUM3MO_DROUGHT3340_Z |   .3694405   .0814908     4.53   0.000     .2091475    .5297335
         ww1_vol_sh_Z |   -.001046   .0192117    -0.05   0.957    -.0388357    .0367436
ww1_awards_pop10_is_Z |   .0066399   .0131083     0.51   0.613    -.0191442    .0324241
             lpop30_Z |  -.1624241   .0426817    -3.81   0.000    -.2463794   -.0784688
           c30unemp_Z |  -.0526289   .0232469    -2.26   0.024    -.0983557   -.0069022
          c30urban1_Z |   .0793414   .0206995     3.83   0.000     .0386253    .1200576
            c30farm_Z |   .0934349   .0641945     1.46   0.146    -.0328362    .2197059
            iYf_T29_Z |   .1848732   .0491854     3.76   0.000     .0881251    .2816213
           MEAN9628_Z |   .1785796   .0500276     3.57   0.000      .080175    .2769841
             c30men_Z |  -.0255953   .0336155    -0.76   0.447    -.0917172    .0405265
           c30black_Z |  -.0526755   .0514622    -1.02   0.307     -.153902    .0485511
             c30jap_Z |   .0012546   .0170185     0.07   0.941    -.0322209    .0347302
             c30deu_Z |   .0312945   .0357373     0.88   0.382     -.039001    .1015901
             c30ita_Z |   -.033184   .0225653    -1.47   0.142      -.07757     .011202
             c30vet_Z |   .0519855   .0244453     2.13   0.034     .0039014    .1000695
           lc40wage_Z |   .0309272   .0439956     0.70   0.483    -.0556124    .1174668
      iwarconpro_PC_Z |  -.0058818    .016143    -0.36   0.716    -.0376353    .0258717
             state1_Z |  -.0222184   .0195765    -1.13   0.257    -.0607255    .0162888
             state2_Z |  -.1296841   .0334566    -3.88   0.000    -.1954934   -.0638747
             state3_Z |   -.028297    .023682    -1.19   0.233    -.0748797    .0182858
             state4_Z |   -.094014   .0205302    -4.58   0.000    -.1343971   -.0536309
             state5_Z |  -.0283338   .0156552    -1.81   0.071    -.0591277    .0024602
             state6_Z |  -.1006297   .0279639    -3.60   0.000    -.1556349   -.0456244
             state7_Z |  -.0263215   .0149296    -1.76   0.079    -.0556881    .0030451
             state8_Z |  -.0561138    .034032    -1.65   0.100     -.123055    .0108274
             state9_Z |  -.2255502   .0534684    -4.22   0.000     -.330723   -.1203774
            state10_Z |  -.2415553    .054362    -4.44   0.000    -.3484858   -.1346248
            state11_Z |  -.1311412    .063295    -2.07   0.039     -.255643   -.0066395
            state12_Z |  -.1726226   .0594983    -2.90   0.004    -.2896561   -.0555891
            state13_Z |  -.2040618   .0561928    -3.63   0.000    -.3145934   -.0935302
            state14_Z |  -.2129448   .0565744    -3.76   0.000    -.3242271   -.1016625
            state15_Z |  -.1533315   .0495019    -3.10   0.002    -.2507021   -.0559609
            state16_Z |  -.0736803   .0535519    -1.38   0.170    -.1790172    .0316566
            state17_Z |  -.0182105   .0672286    -0.27   0.787    -.1504496    .1140286
            state18_Z |  -.1355207   .0616567    -2.20   0.029    -.2567998   -.0142415
            state19_Z |  -.2093006   .0604995    -3.46   0.001    -.3283035   -.0902977
            state20_Z |   -.088217   .0610619    -1.44   0.149    -.2083262    .0318923
            state21_Z |   .0708256   .0421304     1.68   0.094    -.0120451    .1536963
            state22_Z |    .000566   .0464715     0.01   0.990    -.0908437    .0919757
            state23_Z |  -.2611698   .0689904    -3.79   0.000    -.3968744   -.1254651
            state24_Z |  -.1033247   .0451435    -2.29   0.023    -.1921223   -.0145271
            state25_Z |  -.2008563   .0447334    -4.49   0.000    -.2888472   -.1128653
            state26_Z |  -.1917593   .0532377    -3.60   0.000    -.2964782   -.0870404
            state27_Z |  -.1625149   .0763704    -2.13   0.034     -.312736   -.0122938
            state28_Z |  -.0960328    .053342    -1.80   0.073    -.2009568    .0088912
            state29_Z |  -.2079399    .050763    -4.10   0.000    -.3077911   -.1080887
            state30_Z |  -.1699157   .0700744    -2.42   0.016    -.3077526   -.0320789
            state31_Z |  -.1186624   .0455497    -2.61   0.010    -.2082589   -.0290658
            state32_Z |          0  (omitted)
            state33_Z |  -.2840025    .085961    -3.30   0.001    -.4530885   -.1149165
            state34_Z |  -.0643532   .0330519    -1.95   0.052    -.1293665    .0006601
            state35_Z |  -.1101612   .0432043    -2.55   0.011    -.1951443   -.0251781
            state36_Z |  -.2257856   .0603897    -3.74   0.000    -.3445726   -.1069987
            state37_Z |   -.265788   .0509072    -5.22   0.000     -.365923   -.1656531
            state38_Z |  -.0793061    .028025    -2.83   0.005    -.1344315   -.0241808
            state39_Z |  -.1712846   .0475734    -3.60   0.000    -.2648619   -.0777074
            state40_Z |  -.1053094   .0414238    -2.54   0.011    -.1867903   -.0238285
            state41_Z |     -.0577   .0506164    -1.14   0.255    -.1572629    .0418629
            state42_Z |  -.0641226   .0353105    -1.82   0.070    -.1335786    .0053334
            state43_Z |  -.0664803   .0364773    -1.82   0.069    -.1382313    .0052707
            state44_Z |  -.0913961   .0329295    -2.78   0.006    -.1561686   -.0266236
            state45_Z |  -.0071068   .0253536    -0.28   0.779    -.0569775     .042764
            state46_Z |  -.0470789   .0518492    -0.91   0.365    -.1490667    .0549089
            state47_Z |  -.0948678   .0464529    -2.04   0.042    -.1862409   -.0034946
            state48_Z |  -.0936418   .0479627    -1.95   0.052    -.1879849    .0007012
                _cons |  -7.15e-09   .0300112    -0.00   1.000    -.0590323    .0590323
---------------------------------------------------------------------------------------
number of observations (_N) was 0, now 20
(20 missing values generated)
(20 missing values generated)
(20 missing values generated)
(20 missing values generated)
(20 missing values generated)
(20 missing values generated)
(file results/figures/Fig4C-H_pre-AAA.png written in PNG format)
(file results/figures/Fig4C-H_pre-AAA.pdf written in PDF format)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(3,070 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
note: state32_Z omitted because of collinearity

Linear regression                               Number of obs     =      3,022
                                                F(72, 338)        =          .
                                                Prob > F          =          .
                                                R-squared         =     0.6503
                                                Root MSE          =     .59866

                                      (Std. Err. adjusted for 339 clusters in CLIMDIVX)
---------------------------------------------------------------------------------------
                      |               Robust
   iwarbond_1944_PC_Z |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
iSUM3MO_DROUGHT9700_Z |   .0041169   .0277045     0.15   0.882    -.0503782    .0586119
iSUM3MO_DROUGHT0104_Z |   .0057424   .0374241     0.15   0.878    -.0678711     .079356
iSUM3MO_DROUGHT0508_Z |   .0247601   .0290613     0.85   0.395    -.0324037    .0819239
iSUM3MO_DROUGHT0912_Z |   .0116842   .0283918     0.41   0.681    -.0441626     .067531
iSUM3MO_DROUGHT1316_Z |  -.0534113   .0275829    -1.94   0.054    -.1076671    .0008445
iSUM3MO_DROUGHT1720_Z |  -.0619856   .0422443    -1.47   0.143    -.1450805    .0211093
iSUM3MO_DROUGHT2124_Z |  -.0072408   .0240889    -0.30   0.764    -.0546238    .0401421
iSUM3MO_DROUGHT2528_Z |   -.032046   .0326179    -0.98   0.327    -.0962056    .0321136
iSUM3MO_DROUGHT2932_Z |  -.0082859   .0244764    -0.34   0.735    -.0564312    .0398593
iSUM3MO_DROUGHT3340_Z |   .2181674   .0497447     4.39   0.000     .1203193    .3160155
         ww1_vol_sh_Z |   .0016664   .0136248     0.12   0.903    -.0251337    .0284665
ww1_awards_pop10_is_Z |   .0295041   .0132951     2.22   0.027     .0033526    .0556556
             lpop30_Z |  -.0627737   .0436442    -1.44   0.151    -.1486222    .0230747
           c30unemp_Z |  -.0382113   .0165866    -2.30   0.022    -.0708372   -.0055854
          c30urban1_Z |   .0453364   .0193824     2.34   0.020      .007211    .0834619
            c30farm_Z |  -.1651618   .0458895    -3.60   0.000    -.2554266   -.0748969
            iYf_T29_Z |   .1054521   .0313996     3.36   0.001     .0436889    .1672154
           MEAN9628_Z |   .0912902   .0312219     2.92   0.004     .0298765    .1527039
             c30men_Z |   -.046961    .027242    -1.72   0.086    -.1005462    .0066242
           c30black_Z |  -.0921759   .0324906    -2.84   0.005     -.156085   -.0282667
             c30jap_Z |   .0275312      .0133     2.07   0.039       .00137    .0536924
             c30deu_Z |   .0640462   .0211776     3.02   0.003     .0223897    .1057027
             c30ita_Z |  -.0181565   .0209705    -0.87   0.387    -.0594057    .0230927
             c30vet_Z |   .0038712   .0550008     0.07   0.944    -.1043159    .1120582
           lc40wage_Z |   .2280762   .0315847     7.22   0.000     .1659488    .2902036
      iwarconpro_PC_Z |   .2461867   .0212495    11.59   0.000     .2043888    .2879847
             state1_Z |  -.0131243   .0118306    -1.11   0.268    -.0363952    .0101465
             state2_Z |  -.0440691   .0174031    -2.53   0.012    -.0783013    -.009837
             state3_Z |  -.0304747   .0149099    -2.04   0.042    -.0598026   -.0011467
             state4_Z |  -.0264404    .012779    -2.07   0.039    -.0515768   -.0013041
             state5_Z |  -.0296775   .0099041    -3.00   0.003     -.049159    -.010196
             state6_Z |  -.0229594   .0169732    -1.35   0.177    -.0563458    .0104271
             state7_Z |   .0029752   .0077811     0.38   0.702    -.0123303    .0182807
             state8_Z |  -.0333669   .0224859    -1.48   0.139    -.0775969     .010863
             state9_Z |  -.0752785   .0317628    -2.37   0.018    -.1377562   -.0128008
            state10_Z |  -.0632376   .0335011    -1.89   0.060    -.1291345    .0026592
            state11_Z |   -.052274   .0347024    -1.51   0.133    -.1205339    .0159858
            state12_Z |  -.0834134   .0329858    -2.53   0.012    -.1482968     -.01853
            state13_Z |  -.0989822   .0329211    -3.01   0.003    -.1637382   -.0342263
            state14_Z |  -.1140504   .0345856    -3.30   0.001    -.1820805   -.0460203
            state15_Z |  -.0837986   .0319025    -2.63   0.009    -.1465511   -.0210462
            state16_Z |   .0607881   .0337495     1.80   0.073    -.0055974    .1271735
            state17_Z |    .045118   .0383629     1.18   0.240    -.0303421     .120578
            state18_Z |  -.0025347   .0361777    -0.07   0.944    -.0736966    .0686271
            state19_Z |  -.0911552   .0377783    -2.41   0.016    -.1654655   -.0168449
            state20_Z |   .0323306    .035185     0.92   0.359    -.0368786    .1015399
            state21_Z |   .0809746   .0327814     2.47   0.014     .0164933    .1454559
            state22_Z |   .0183697   .0291342     0.63   0.529    -.0389375    .0756769
            state23_Z |  -.0576236   .0414069    -1.39   0.165    -.1390714    .0238241
            state24_Z |  -.0200197    .027527    -0.73   0.468    -.0741656    .0341261
            state25_Z |  -.1628789   .0233802    -6.97   0.000     -.208868   -.1168898
            state26_Z |  -.0591703   .0312994    -1.89   0.060    -.1207364    .0023957
            state27_Z |  -.1041301   .0445215    -2.34   0.020    -.1917043   -.0165559
            state28_Z |  -.0831161   .0288138    -2.88   0.004     -.139793   -.0264392
            state29_Z |  -.0670906   .0299529    -2.24   0.026    -.1260083    -.008173
            state30_Z |  -.0834079   .0398907    -2.09   0.037    -.1618732   -.0049425
            state31_Z |  -.1202643   .0251801    -4.78   0.000    -.1697938   -.0707348
            state32_Z |          0  (omitted)
            state33_Z |  -.1844614    .059408    -3.10   0.002    -.3013174   -.0676055
            state34_Z |  -.0351775   .0206041    -1.71   0.089     -.075706    .0053509
            state35_Z |  -.0479048   .0256271    -1.87   0.062    -.0983135     .002504
            state36_Z |  -.1064849   .0352777    -3.02   0.003    -.1758765   -.0370934
            state37_Z |  -.0966681   .0292875    -3.30   0.001    -.1542769   -.0390593
            state38_Z |  -.0337173    .016194    -2.08   0.038    -.0655711   -.0018635
            state39_Z |  -.0809689   .0278276    -2.91   0.004     -.135706   -.0262318
            state40_Z |  -.0268167    .024453    -1.10   0.274    -.0749159    .0212824
            state41_Z |   .0545478   .0310166     1.76   0.080    -.0064621    .1155577
            state42_Z |  -.0095953   .0215703    -0.44   0.657    -.0520243    .0328337
            state43_Z |  -.0682106   .0250087    -2.73   0.007    -.1174029   -.0190183
            state44_Z |  -.0642477   .0194737    -3.30   0.001    -.1025526   -.0259427
            state45_Z |   .0187086   .0146453     1.28   0.202    -.0100989    .0475161
            state46_Z |  -.0052083   .0326119    -0.16   0.873    -.0693561    .0589395
            state47_Z |   .0419984   .0248101     1.69   0.091    -.0068032    .0908001
            state48_Z |   .0325823   .0314017     1.04   0.300    -.0291851    .0943496
                _cons |  -5.27e-09   .0183797    -0.00   1.000     -.036153     .036153
---------------------------------------------------------------------------------------
number of observations (_N) was 0, now 20
(20 missing values generated)
(20 missing values generated)
(20 missing values generated)
(20 missing values generated)
(20 missing values generated)
(20 missing values generated)
(file results/figures/Fig4C-H_pre-bond.png written in PNG format)
(file results/figures/Fig4C-H_pre-bond.pdf written in PDF format)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(3,070 missing values generated)
(3,070 missing values generated)
(3,070 missing values generated)
(3,070 missing values generated)
(3,070 missing values generated)
(3,070 missing values generated)
(3,070 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(3,070 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(3,070 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(3,070 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
note: state32_Z omitted because of collinearity

Linear regression                               Number of obs     =      2,329
                                                F(63, 265)        =          .
                                                Prob > F          =          .
                                                R-squared         =     0.6376
                                                Root MSE          =     .61048

                                      (Std. Err. adjusted for 266 clusters in CLIMDIVX)
---------------------------------------------------------------------------------------
                      |               Robust
      ww2_vol_pop40_Z |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
iSUM3MO_DROUGHT9700_Z |  -.0044354   .0277313    -0.16   0.873    -.0590371    .0501662
iSUM3MO_DROUGHT0104_Z |  -.1037605   .0323419    -3.21   0.001    -.1674402   -.0400808
iSUM3MO_DROUGHT0508_Z |   .0013862   .0259578     0.05   0.957    -.0497236     .052496
iSUM3MO_DROUGHT0912_Z |  -.0311449   .0559788    -0.56   0.578    -.1413648     .079075
iSUM3MO_DROUGHT1316_Z |  -.1101878   .0442925    -2.49   0.013    -.1973977   -.0229779
iSUM3MO_DROUGHT1720_Z |   -.013757   .0513976    -0.27   0.789    -.1149566    .0874425
iSUM3MO_DROUGHT2124_Z |  -.0004162   .0329755    -0.01   0.990    -.0653436    .0645112
iSUM3MO_DROUGHT2528_Z |   .0001316   .0560489     0.00   0.998    -.1102263    .1104894
iSUM3MO_DROUGHT2932_Z |   .0626354    .039192     1.60   0.111     -.014532    .1398028
iSUM3MO_DROUGHT3340_Z |    .124671   .0642203     1.94   0.053    -.0017761     .251118
         ww1_vol_sh_Z |   .0738077   .0205043     3.60   0.000     .0334357    .1141797
ww1_awards_pop10_is_Z |   .0303249    .026048     1.16   0.245    -.0209624    .0816123
             lpop30_Z |  -.0361136   .0370185    -0.98   0.330    -.1090015    .0367742
           c30unemp_Z |    .062607   .0239689     2.61   0.010     .0154132    .1098007
          c30urban1_Z |   .0176366   .0172973     1.02   0.309    -.0164211    .0516942
            c30farm_Z |  -.0860833   .0381852    -2.25   0.025    -.1612683   -.0108983
            iYf_T29_Z |  -.0382498   .0345432    -1.11   0.269    -.1062639    .0297643
           MEAN9628_Z |   .0041458   .0436591     0.09   0.924    -.0818172    .0901087
             c30men_Z |  -.0956442   .0334777    -2.86   0.005    -.1615604    -.029728
           c30black_Z |   -.271816   .0434229    -6.26   0.000    -.3573137   -.1863182
             c30jap_Z |   .0081132   .0202944     0.40   0.690    -.0318456    .0480719
             c30deu_Z |  -.0906654   .0280939    -3.23   0.001     -.145981   -.0353498
             c30ita_Z |  -.0253484   .0201766    -1.26   0.210    -.0650752    .0143784
             c30vet_Z |   .1088556   .0282244     3.86   0.000      .053283    .1644281
           lc40wage_Z |   .1719876   .0393558     4.37   0.000     .0944978    .2494775
      iwarconpro_PC_Z |  -.0605122    .014446    -4.19   0.000    -.0889559   -.0320686
             state1_Z |  -.1011735   .0180221    -5.61   0.000    -.1366583   -.0656888
             state2_Z |  -.1541094   .0240275    -6.41   0.000    -.2014185   -.1068002
             state3_Z |  -.1159965   .0209411    -5.54   0.000    -.1572286   -.0747644
             state4_Z |  -.0664867   .0169026    -3.93   0.000    -.0997672   -.0332062
             state5_Z |  -.0832169   .0143585    -5.80   0.000    -.1114883   -.0549456
             state6_Z |   -.055975   .0216446    -2.59   0.010    -.0985922   -.0133577
             state7_Z |  -.0863191   .0104772    -8.24   0.000    -.1069483   -.0656899
             state8_Z |  -.1969953   .0304058    -6.48   0.000    -.2568631   -.1371276
             state9_Z |  -.2859001   .0518408    -5.51   0.000    -.3879723   -.1838279
            state10_Z |  -.4317447   .0497445    -8.68   0.000    -.5296895      -.3338
            state11_Z |   -.336711   .0631694    -5.33   0.000    -.4610888   -.2123331
            state12_Z |  -.4136018   .0620433    -6.67   0.000    -.5357623   -.2914414
            state13_Z |  -.3998607   .0571524    -7.00   0.000    -.5123913   -.2873301
            state14_Z |  -.4408349    .059617    -7.39   0.000    -.5582181   -.3234516
            state15_Z |  -.2459149   .0494333    -4.97   0.000    -.3432469    -.148583
            state23_Z |  -.4879328   .0572282    -8.53   0.000    -.6006127    -.375253
            state24_Z |  -.1995473   .0429273    -4.65   0.000    -.2840694   -.1150253
            state25_Z |  -.4490446    .050539    -8.89   0.000    -.5485536   -.3495356
            state26_Z |  -.1861991   .0410891    -4.53   0.000    -.2671018   -.1052965
            state27_Z |  -.2701072   .0600854    -4.50   0.000    -.3884128   -.1518016
            state28_Z |  -.3606091   .0372886    -9.67   0.000    -.4340288   -.2871894
            state29_Z |  -.2435658   .0458698    -5.31   0.000    -.3338814   -.1532503
            state30_Z |  -.3830424   .0538029    -7.12   0.000    -.4889779   -.2771069
            state31_Z |  -.2253006   .0402768    -5.59   0.000    -.3046038   -.1459974
            state32_Z |          0  (omitted)
            state33_Z |  -.3523618   .0642796    -5.48   0.000    -.4789255   -.2257982
            state34_Z |   -.262293   .0279447    -9.39   0.000    -.3173149   -.2072711
            state35_Z |  -.2395441   .0448276    -5.34   0.000    -.3278077   -.1512805
            state36_Z |  -.3708591   .0560451    -6.62   0.000    -.4812094   -.2605088
            state37_Z |  -.2647273   .0440047    -6.02   0.000    -.3513706    -.178084
            state38_Z |  -.2188389   .0224161    -9.76   0.000    -.2629752   -.1747025
            state40_Z |  -.2847251   .0458614    -6.21   0.000    -.3750241    -.194426
            state41_Z |  -.2128981   .0516732    -4.12   0.000    -.3146405   -.1111558
            state42_Z |  -.2086558    .028396    -7.35   0.000    -.2645664   -.1527453
            state43_Z |  -.1486147   .0258398    -5.75   0.000     -.199492   -.0977373
            state44_Z |  -.2719484   .0308348    -8.82   0.000    -.3326607   -.2112361
            state46_Z |  -.2715816   .0582071    -4.67   0.000     -.386189   -.1569743
            state47_Z |  -.2986067    .040204    -7.43   0.000    -.3777667   -.2194467
            state48_Z |  -.2291569   .0373927    -6.13   0.000    -.3027816   -.1555323
                _cons |   1.30e-08   .0242454     0.00   1.000    -.0477381    .0477382
---------------------------------------------------------------------------------------
number of observations (_N) was 0, now 20
(20 missing values generated)
(20 missing values generated)
(20 missing values generated)
(20 missing values generated)
(20 missing values generated)
(20 missing values generated)
(file results/figures/Fig4C-H_pre-volunteer_wwii.png written in PNG format)
(file results/figures/Fig4C-H_pre-volunteer_wwii.pdf written in PDF format)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(3,070 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
note: state32_Z omitted because of collinearity

Linear regression                               Number of obs     =      3,022
                                                F(59, 338)        =          .
                                                Prob > F          =          .
                                                R-squared         =     0.2222
                                                Root MSE          =      .8908

                                      (Std. Err. adjusted for 339 clusters in CLIMDIVX)
---------------------------------------------------------------------------------------
                      |               Robust
      ww1_vol_pop10_Z |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
iSUM3MO_DROUGHT9700_Z |  -.0310077   .0281818    -1.10   0.272    -.0864416    .0244261
iSUM3MO_DROUGHT0104_Z |  -.0350248   .0276292    -1.27   0.206    -.0893717    .0193222
iSUM3MO_DROUGHT0508_Z |   .0160368   .0525603     0.31   0.760    -.0873498    .1194233
iSUM3MO_DROUGHT0912_Z |   -.032323   .0286978    -1.13   0.261    -.0887718    .0241258
iSUM3MO_DROUGHT1316_Z |  -.0325434   .0342807    -0.95   0.343    -.0999737     .034887
             lpop10_Z |   .1057851   .0370505     2.86   0.005     .0329064    .1786638
           c10unemp_Z |    .028541   .0193677     1.47   0.142    -.0095554    .0666373
          c10urban1_Z |   .0833396   .0217925     3.82   0.000     .0404736    .1262056
             c10men_Z |   .0660573   .0497304     1.33   0.185    -.0317629    .1638774
           c10black_Z |  -.1033374   .0269544    -3.83   0.000     -.156357   -.0503179
             c10jap_Z |  -.0405618   .0297982    -1.36   0.174     -.099175    .0180514
             c10deu_Z |   .0360869   .0285616     1.26   0.207     -.020094    .0922678
             c10ita_Z |  -.0199941   .0222891    -0.90   0.370    -.0638369    .0238487
             state1_Z |  -.0014627    .009423    -0.16   0.877    -.0199977    .0170724
             state2_Z |   .0109262   .0178306     0.61   0.540    -.0241468    .0459992
             state3_Z |   -.005742   .0140645    -0.41   0.683     -.033407     .021923
             state4_Z |   .0196168   .0095739     2.05   0.041     .0007849    .0384488
             state5_Z |   .0323214   .0074508     4.34   0.000     .0176656    .0469771
             state6_Z |   .0089395   .0109605     0.82   0.415      -.01262     .030499
             state7_Z |  -.0004425   .0103254    -0.04   0.966    -.0207525    .0198675
             state8_Z |   -.018763   .0162438    -1.16   0.249    -.0507147    .0131886
             state9_Z |  -.0569373   .0222336    -2.56   0.011     -.100671   -.0132036
            state10_Z |  -.0427587     .02286    -1.87   0.062    -.0877245    .0022071
            state11_Z |  -.0787184   .0259896    -3.03   0.003    -.1298402   -.0275967
            state12_Z |  -.0520506   .0273202    -1.91   0.058    -.1057896    .0016884
            state13_Z |  -.0883317   .0220542    -4.01   0.000    -.1317125   -.0449509
            state14_Z |  -.0181775   .0236331    -0.77   0.442    -.0646641     .028309
            state15_Z |   .0285377    .025973     1.10   0.273    -.0225513    .0796268
            state16_Z |   .0054397   .0272009     0.20   0.842    -.0480647    .0589441
            state17_Z |   .0435327    .030666     1.42   0.157    -.0167875    .1038529
            state18_Z |  -.0688152   .0228529    -3.01   0.003     -.113767   -.0238634
            state19_Z |  -.0629785   .0293764    -2.14   0.033    -.1207621    -.005195
            state20_Z |  -.0161859   .0212105    -0.76   0.446    -.0579072    .0255353
            state21_Z |  -.0171617   .0215169    -0.80   0.426    -.0594856    .0251623
            state22_Z |   .0639283   .0194153     3.29   0.001     .0257383    .1021183
            state23_Z |  -.0596756   .0269794    -2.21   0.028    -.1127443   -.0066068
            state24_Z |  -.0100248   .0311794    -0.32   0.748     -.071355    .0513054
            state25_Z |   .0005431   .0223323     0.02   0.981    -.0433848    .0444709
            state26_Z |    .084322   .0479833     1.76   0.080    -.0100615    .1787054
            state27_Z |  -.0117245   .0373145    -0.31   0.754    -.0851224    .0616734
            state28_Z |  -.0392453   .0223965    -1.75   0.081    -.0832994    .0048088
            state29_Z |   -.002109   .0314783    -0.07   0.947    -.0640271    .0598091
            state30_Z |  -.0517818   .0265093    -1.95   0.052    -.1039257    .0003621
            state31_Z |  -.0230833   .0219001    -1.05   0.293     -.066161    .0199943
            state32_Z |          0  (omitted)
            state33_Z |  -.0554544   .0278039    -1.99   0.047    -.1101449   -.0007639
            state34_Z |   .0300203   .0255664     1.17   0.241     -.020269    .0803096
            state35_Z |  -.0957862   .0209075    -4.58   0.000    -.1369113   -.0546611
            state36_Z |  -.0679218   .0311843    -2.18   0.030    -.1292615   -.0065821
            state37_Z |  -.0207864   .0202717    -1.03   0.306     -.060661    .0190883
            state38_Z |   .0219689    .014762     1.49   0.138     -.007068    .0510058
            state39_Z |   .0434049    .024455     1.77   0.077    -.0046983     .091508
            state40_Z |   .1233936   .0280528     4.40   0.000     .0682135    .1785737
            state41_Z |   .0850534    .057103     1.49   0.137    -.0272687    .1973755
            state42_Z |  -.0073267   .0224083    -0.33   0.744     -.051404    .0367505
            state43_Z |   .0296779   .0335079     0.89   0.376    -.0362325    .0955883
            state44_Z |   .0223435   .0198519     1.13   0.261    -.0167053    .0613922
            state45_Z |   .2388741    .055402     4.31   0.000     .1298979    .3478503
            state46_Z |  -.0106676   .0392124    -0.27   0.786    -.0877987    .0664635
            state47_Z |   .1332324   .0196863     6.77   0.000     .0945093    .1719555
            state48_Z |  -.0589813   .0190218    -3.10   0.002    -.0963974   -.0215653
                _cons |   6.92e-10   .0183066     0.00   1.000    -.0360093    .0360093
---------------------------------------------------------------------------------------
number of observations (_N) was 0, now 20
(20 missing values generated)
(20 missing values generated)
(20 missing values generated)
(20 missing values generated)
(20 missing values generated)
(20 missing values generated)
(file results/figures/Fig4C-H_pre-volunteer_wwi.png written in PNG format)
(file results/figures/Fig4C-H_pre-volunteer_wwi.pdf written in PDF format)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(3,070 missing values generated)
(3,070 missing values generated)
(3,070 missing values generated)
(3,070 missing values generated)
(3,070 missing values generated)
(3,070 missing values generated)
(3,070 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(3,070 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(3,070 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(3,070 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
(741 missing values generated)
note: state32_Z omitted because of collinearity

Linear regression                               Number of obs     =      2,329
                                                F(63, 265)        =          .
                                                Prob > F          =          .
                                                R-squared         =     0.1887
                                                Root MSE          =     .91336

                                      (Std. Err. adjusted for 266 clusters in CLIMDIVX)
---------------------------------------------------------------------------------------
                      |               Robust
ww2_awards_pop40_is_Z |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
iSUM3MO_DROUGHT9700_Z |  -.0376457   .0316042    -1.19   0.235     -.099873    .0245817
iSUM3MO_DROUGHT0104_Z |   .0057298   .0236999     0.24   0.809    -.0409343    .0523939
iSUM3MO_DROUGHT0508_Z |   .0202295   .0443681     0.46   0.649    -.0671293    .1075882
iSUM3MO_DROUGHT0912_Z |   .0204866   .0416428     0.49   0.623    -.0615064    .1024795
iSUM3MO_DROUGHT1316_Z |  -.0211887   .0368797    -0.57   0.566    -.0938031    .0514257
iSUM3MO_DROUGHT1720_Z |   .0751807   .0806019     0.93   0.352    -.0835209    .2338823
iSUM3MO_DROUGHT2124_Z |   .0058709   .0395691     0.15   0.882     -.072039    .0837808
iSUM3MO_DROUGHT2528_Z |  -.0526302   .0375332    -1.40   0.162    -.1265314     .021271
iSUM3MO_DROUGHT2932_Z |    .000775   .0456415     0.02   0.986    -.0890911    .0906412
iSUM3MO_DROUGHT3340_Z |   .1108809   .0365131     3.04   0.003     .0389881    .1827737
         ww1_vol_sh_Z |   .1073002   .0371667     2.89   0.004     .0341206    .1804797
ww1_awards_pop10_is_Z |   .0256361   .0272012     0.94   0.347    -.0279218     .079194
             lpop30_Z |  -.1513859   .1133608    -1.34   0.183    -.3745883    .0718165
           c30unemp_Z |   .0433411   .0499211     0.87   0.386    -.0549513    .1416336
          c30urban1_Z |   .0282759   .0244354     1.16   0.248    -.0198362    .0763881
            c30farm_Z |   .0466058   .0447301     1.04   0.298    -.0414658    .1346775
            iYf_T29_Z |   .1017132   .0617302     1.65   0.101    -.0198309    .2232572
           MEAN9628_Z |   .0018238   .0567008     0.03   0.974    -.1098177    .1134652
             c30men_Z |  -.0977082   .0395283    -2.47   0.014    -.1755376   -.0198787
           c30black_Z |  -.0915106   .0389471    -2.35   0.020    -.1681957   -.0148255
             c30jap_Z |   .0296995   .0421263     0.71   0.481    -.0532454    .1126444
             c30deu_Z |   .0211409    .050434     0.42   0.675    -.0781614    .1204433
             c30ita_Z |  -.0136376   .0383521    -0.36   0.722    -.0891512    .0618761
             c30vet_Z |   .0730704    .031169     2.34   0.020     .0116999    .1344409
           lc40wage_Z |   .1478018     .05865     2.52   0.012     .0323225    .2632811
      iwarconpro_PC_Z |   .0266909   .0220714     1.21   0.228    -.0167667    .0701486
             state1_Z |   .0101121   .0172679     0.59   0.559    -.0238876    .0441118
             state2_Z |  -.0156916   .0228785    -0.69   0.493    -.0607384    .0293552
             state3_Z |   .0100474   .0200568     0.50   0.617    -.0294436    .0495384
             state4_Z |  -.0108083    .016144    -0.67   0.504    -.0425952    .0209786
             state5_Z |   .0293092   .0128358     2.28   0.023     .0040362    .0545823
             state6_Z |  -.0094403   .0214287    -0.44   0.660    -.0516325    .0327519
             state7_Z |  -.0072572   .0105484    -0.69   0.492    -.0280265     .013512
             state8_Z |  -.0118199   .0258351    -0.46   0.648    -.0626881    .0390482
             state9_Z |  -.0050843   .0435945    -0.12   0.907    -.0909201    .0807514
            state10_Z |  -.0389164   .0429423    -0.91   0.366    -.1234679     .045635
            state11_Z |  -.0639383   .0557273    -1.15   0.252     -.173663    .0457864
            state12_Z |  -.0957573   .0490897    -1.95   0.052    -.1924127    .0008981
            state13_Z |  -.0626473   .0525698    -1.19   0.234    -.1661549    .0408603
            state14_Z |  -.0391291   .0478739    -0.82   0.414    -.1333906    .0551325
            state15_Z |  -.1044919   .0585688    -1.78   0.076    -.2198113    .0108275
            state23_Z |  -.0072406   .0527819    -0.14   0.891    -.1111659    .0966847
            state24_Z |   .0213495   .0401754     0.53   0.596    -.0577541    .1004532
            state25_Z |  -.0595392   .0316739    -1.88   0.061    -.1219038    .0028254
            state26_Z |   .0318617   .0477416     0.67   0.505    -.0621395     .125863
            state27_Z |   .0088897   .0595169     0.15   0.881    -.1082964    .1260758
            state28_Z |  -.0222372   .0255448    -0.87   0.385    -.0725337    .0280593
            state29_Z |   .0224384   .0311697     0.72   0.472    -.0389335    .0838102
            state30_Z |  -.0216813   .0511706    -0.42   0.672    -.1224339    .0790713
            state31_Z |  -.0030287   .0420998    -0.07   0.943    -.0859214    .0798641
            state32_Z |          0  (omitted)
            state33_Z |  -.0399707   .0503591    -0.79   0.428    -.1391256    .0591842
            state34_Z |  -.0070602   .0282964    -0.25   0.803    -.0627747    .0486543
            state35_Z |  -.0414964   .0257913    -1.61   0.109    -.0922782    .0092855
            state36_Z |  -.0151177   .0466727    -0.32   0.746    -.1070142    .0767789
            state37_Z |  -.0144745   .0381361    -0.38   0.705    -.0895628    .0606138
            state38_Z |   .0214728   .0281761     0.76   0.447    -.0340046    .0769503
            state40_Z |  -.0096836   .0445787    -0.22   0.828     -.097457    .0780899
            state41_Z |   .1145966   .0693473     1.65   0.100    -.0219452    .2511384
            state42_Z |   .0101884   .0386565     0.26   0.792    -.0659245    .0863013
            state43_Z |  -.0048721   .0315197    -0.15   0.877     -.066933    .0571888
            state44_Z |   .0062437   .0314545     0.20   0.843    -.0556888    .0681763
            state46_Z |   .1027322   .0874905     1.17   0.241    -.0695328    .2749972
            state47_Z |  -.0059561   .0387284    -0.15   0.878    -.0822107    .0702984
            state48_Z |   .0386515   .0377525     1.02   0.307    -.0356815    .1129844
                _cons |  -3.96e-09   .0212382    -0.00   1.000     -.041817     .041817
---------------------------------------------------------------------------------------
number of observations (_N) was 0, now 20
(20 missing values generated)
(20 missing values generated)
(20 missing values generated)
(20 missing values generated)
(20 missing values generated)
(20 missing values generated)
(file results/figures/Fig4C-H_pre-medal_wwii.png written in PNG format)
(file results/figures/Fig4C-H_pre-medal_wwii.pdf written in PDF format)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(3,070 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
(48 missing values generated)
note: state32_Z omitted because of collinearity

Linear regression                               Number of obs     =      3,022
                                                F(59, 338)        =          .
                                                Prob > F          =          .
                                                R-squared         =     0.0983
                                                Root MSE          =     .95915

                                      (Std. Err. adjusted for 339 clusters in CLIMDIVX)
---------------------------------------------------------------------------------------
                      |               Robust
ww1_awards_pop10_is_Z |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
iSUM3MO_DROUGHT9700_Z |   .0670432   .0250875     2.67   0.008      .017696    .1163904
iSUM3MO_DROUGHT0104_Z |  -.0465921   .0314881    -1.48   0.140    -.1085296    .0153453
iSUM3MO_DROUGHT0508_Z |   .0709908   .0540154     1.31   0.190     -.035258    .1772395
iSUM3MO_DROUGHT0912_Z |   .0328828   .0398294     0.83   0.410    -.0454619    .1112274
iSUM3MO_DROUGHT1316_Z |     .00727   .0297614     0.24   0.807    -.0512708    .0658108
             lpop10_Z |   .0555339   .0279523     1.99   0.048     .0005515    .1105162
           c10unemp_Z |  -.0088475   .0196017    -0.45   0.652    -.0474043    .0297092
          c10urban1_Z |   .0392941   .0217347     1.81   0.072    -.0034582    .0820464
             c10men_Z |   .1071775   .0433265     2.47   0.014     .0219539    .1924011
           c10black_Z |  -.0748982   .0250188    -2.99   0.003    -.1241104   -.0256861
             c10jap_Z |   .0399463   .0324881     1.23   0.220    -.0239579    .1038506
             c10deu_Z |   .0133653   .0235216     0.57   0.570    -.0329019    .0596325
             c10ita_Z |  -.0063613   .0241722    -0.26   0.793    -.0539081    .0411855
             state1_Z |   .0108003   .0102269     1.06   0.292    -.0093161    .0309168
             state2_Z |   .0136977   .0119621     1.15   0.253    -.0098318    .0372271
             state3_Z |   .0348009   .0127776     2.72   0.007     .0096671    .0599346
             state4_Z |  -.0028076    .013677    -0.21   0.837    -.0297103    .0240952
             state5_Z |   .0210165   .0083367     2.52   0.012     .0046182    .0374149
             state6_Z |   .0061474   .0137395     0.45   0.655    -.0208782    .0331731
             state7_Z |  -.0053917   .0083267    -0.65   0.518    -.0217704     .010987
             state8_Z |   .0233242    .016049     1.45   0.147    -.0082443    .0548927
             state9_Z |   .0263342   .0278418     0.95   0.345    -.0284307    .0810992
            state10_Z |   .0246814   .0261485     0.94   0.346     -.026753    .0761157
            state11_Z |   .0181725   .0318486     0.57   0.569    -.0444738    .0808189
            state12_Z |  -.0210478    .029276    -0.72   0.473    -.0786339    .0365383
            state13_Z |    .036426   .0313749     1.16   0.246    -.0252887    .0981408
            state14_Z |  -.0182573   .0274482    -0.67   0.506    -.0722481    .0357335
            state15_Z |  -.0197749   .0249613    -0.79   0.429    -.0688739     .029324
            state16_Z |  -.0036738   .0279922    -0.13   0.896    -.0587346     .051387
            state17_Z |   .0220723    .037448     0.59   0.556    -.0515882    .0957327
            state18_Z |  -.0503023   .0245458    -2.05   0.041    -.0985841   -.0020205
            state19_Z |   .0078862   .0321821     0.25   0.807    -.0554163    .0711886
            state20_Z |  -.0273951   .0343999    -0.80   0.426    -.0950599    .0402697
            state21_Z |  -.0602909    .020129    -3.00   0.003    -.0998849   -.0206969
            state22_Z |   .0100492   .0445484     0.23   0.822    -.0775778    .0976762
            state23_Z |   .0534732   .0373858     1.43   0.154     -.020065    .1270114
            state24_Z |  -.0046742    .025408    -0.18   0.854    -.0546519    .0453035
            state25_Z |   -.040454   .0240963    -1.68   0.094    -.0878517    .0069436
            state26_Z |  -.0309866   .0310533    -1.00   0.319    -.0920688    .0300956
            state27_Z |  -.0453583   .0339176    -1.34   0.182    -.1120745    .0213579
            state28_Z |  -.0240854   .0223883    -1.08   0.283    -.0681234    .0199526
            state29_Z |  -.0471918   .0288802    -1.63   0.103    -.1039994    .0096157
            state30_Z |   .0850153    .032737     2.60   0.010     .0206214    .1494093
            state31_Z |   .0340588   .0219933     1.55   0.122    -.0092021    .0773197
            state32_Z |          0  (omitted)
            state33_Z |   .0090843    .033311     0.27   0.785    -.0564387    .0746072
            state34_Z |   .0311646   .0190819     1.63   0.103    -.0063696    .0686988
            state35_Z |  -.0044735   .0219538    -0.20   0.839    -.0476568    .0387098
            state36_Z |   .0588453   .0422883     1.39   0.165    -.0243361    .1420266
            state37_Z |  -.0290495   .0253594    -1.15   0.253    -.0789317    .0208326
            state38_Z |   .0195649   .0143336     1.36   0.173    -.0086295    .0477592
            state39_Z |  -.0100772   .0310311    -0.32   0.746    -.0711156    .0509611
            state40_Z |   .0601507   .0304426     1.98   0.049       .00027    .1200315
            state41_Z |   .0839067   .0517354     1.62   0.106    -.0178573    .1856706
            state42_Z |   .0409261    .037108     1.10   0.271    -.0320656    .1139178
            state43_Z |  -.0033007   .0133347    -0.25   0.805    -.0295302    .0229289
            state44_Z |  -.0066874   .0232937    -0.29   0.774    -.0525062    .0391315
            state45_Z |  -.0114196   .0257321    -0.44   0.657     -.062035    .0391957
            state46_Z |  -.0510952   .0303967    -1.68   0.094    -.1108858    .0086954
            state47_Z |  -.0396679   .0271503    -1.46   0.145    -.0930728     .013737
            state48_Z |  -.0244832   .0238523    -1.03   0.305    -.0714008    .0224344
                _cons |   8.14e-09   .0191687     0.00   1.000    -.0377049    .0377049
---------------------------------------------------------------------------------------
number of observations (_N) was 0, now 20
(20 missing values generated)
(20 missing values generated)
(20 missing values generated)
(20 missing values generated)
(20 missing values generated)
(20 missing values generated)
(file results/figures/Fig4C-H_pre-medal_wwi.png written in PNG format)
(file results/figures/Fig4C-H_pre-medal_wwi.pdf written in PDF format)

. 
. ***************************************************************************************************
. ****     III. Erase junk                                                                           ****      *********************************
> ******************************************************************
. 
. erase "tmp/patriot.dta"

. erase "tmp/asn.dta"

. 
. rmdir "tmp/"

. 
. log close
      name:  <unnamed>
       log:  C:\Users\locasa\Dropbox\Patriotism\writeup\submission\QJE\replication\log/results-main.log
  log type:  text
 closed on:  15 Jun 2022, 15:28:23
------------------------------------------------------------------------------------------------------------------------------------------------
